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https://aclanthology.org/2023.emnlp-main.501.bib | https://aclanthology.org/2023.emnlp-main.501/ | @inproceedings{han-etal-2023-dialcot,
title = "{D}ial{C}o{T} Meets {PPO}: Decomposing and Exploring Reasoning Paths in Smaller Language Models",
author = "Han, Chengcheng and
Du, Xiaowei and
Zhang, Che and
Lian, Yixin and
Li, Xiang and
Gao, Ming and
Wang, Baoyuan",
... | Chain-of-Thought (CoT) prompting has successfully enhanced the reasoning capabilities of Large Language Models (LLMs) with at least 100 billion parameters. However, it is ineffective, or even detrimental, to the performance on reasoning tasks in Smaller Language Models (SLMs) with less than 10 billion parameters. In th... | [
"Han, Chengcheng",
"Du, Xiaowei",
"Zhang, Che",
"Lian, Yixin",
"Li, Xiang",
"Gao, Ming",
"Wang, Baoyuan"
] | DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models | emnlp-main.501 | 2310.05074 | [
"https://github.com/hccngu/dialcot"
] | https://huggingface.co/papers/2310.05074 | 0 | 1 | 0 | 7 | [] | [] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.502.bib | https://aclanthology.org/2023.emnlp-main.502/ | @inproceedings{svete-cotterell-2023-recurrent,
title = "Recurrent Neural Language Models as Probabilistic Finite-state Automata",
author = "Svete, Anej and
Cotterell, Ryan",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on... | Studying language models (LMs) in terms of well-understood formalisms allows us to precisely characterize their abilities and limitations. Previous work has investigated the expressive power of recurrent neural network (RNN) LMs in terms of their capacity to recognize unweighted formal languages. However, LMs do not de... | [
"Svete, Anej",
"Cotterell, Ryan"
] | Recurrent Neural Language Models as Probabilistic Finite-state Automata | emnlp-main.502 | 2310.05161 | [
"https://github.com/rycolab/weighted-minsky"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.503.bib | https://aclanthology.org/2023.emnlp-main.503/ | @inproceedings{li-etal-2023-revisiting,
title = "Revisiting Source Context in Nearest Neighbor Machine Translation",
author = "Li, Xuanhong and
Li, Peng and
Hu, Po",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on ... | Nearest neighbor machine translation ($k$NN-MT), which interpolates target token probabilities with estimates derived from additional examples, has achieved significant improvements and attracted extensive interest in recent years. However, existing research does not explicitly consider the source context when retrievi... | [
"Li, Xuanhong",
"Li, Peng",
"Hu, Po"
] | Revisiting Source Context in Nearest Neighbor Machine Translation | emnlp-main.503 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.504.bib | https://aclanthology.org/2023.emnlp-main.504/ | @inproceedings{oguz-etal-2023-find,
title = "Find-2-Find: Multitask Learning for Anaphora Resolution and Object Localization",
author = "Oguz, Cennet and
Denis, Pascal and
Vincent, Emmanuel and
Ostermann, Simon and
van Genabith, Josef",
editor = "Bouamor, Houda and
Pino, J... | In multimodal understanding tasks, visual and linguistic ambiguities can arise. Visual ambiguity can occur when visual objects require a model to ground a referring expression in a video without strong supervision, while linguistic ambiguity can occur from changes in entities in action flows. As an example from the coo... | [
"Oguz, Cennet",
"Denis, Pascal",
"Vincent, Emmanuel",
"Ostermann, Simon",
"van Genabith, Josef"
] | Find-2-Find: Multitask Learning for Anaphora Resolution and Object Localization | emnlp-main.504 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.505.bib | https://aclanthology.org/2023.emnlp-main.505/ | @inproceedings{pratapa-etal-2023-background,
title = "Background Summarization of Event Timelines",
author = "Pratapa, Adithya and
Small, Kevin and
Dreyer, Markus",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on E... | Generating concise summaries of news events is a challenging natural language processing task. While journalists often curate timelines to highlight key sub-events, newcomers to a news event face challenges in catching up on its historical context. In this paper, we address this need by introducing the task of backgrou... | [
"Pratapa, Adithya",
"Small, Kevin",
"Dreyer, Markus"
] | Background Summarization of Event Timelines | emnlp-main.505 | 2310.16197 | [
"https://github.com/amazon-science/background-summaries"
] | https://huggingface.co/papers/2310.16197 | 0 | 0 | 0 | 3 | [] | [
"adithya7/background-summaries"
] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.506.bib | https://aclanthology.org/2023.emnlp-main.506/ | @inproceedings{berdicevskis-etal-2023-superlim,
title = "Superlim: A {S}wedish Language Understanding Evaluation Benchmark",
author = {Berdicevskis, Aleksandrs and
Bouma, Gerlof and
Kurtz, Robin and
Morger, Felix and
{\"O}hman, Joey and
Adesam, Yvonne and
Borin, Lars a... | We present Superlim, a multi-task NLP benchmark and analysis platform for evaluating Swedish language models, a counterpart to the English-language (Super)GLUE suite. We describe the dataset, the tasks, the leaderboard and report the baseline results yielded by a reference implementation. The tested models do not appro... | [
"Berdicevskis, Aleks",
"rs",
"Bouma, Gerlof",
"Kurtz, Robin",
"Morger, Felix",
"{\\\"O}hman, Joey",
"Adesam, Yvonne",
"Borin, Lars",
"Dann{\\'e}lls, Dana",
"Forsberg, Markus",
"Isbister, Tim",
"Lindahl, Anna",
"Malmsten, Martin",
"Rekathati, Faton",
"Sahlgren, Magnus",
"Volodina, Elena... | Superlim: A Swedish Language Understanding Evaluation Benchmark | emnlp-main.506 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.507.bib | https://aclanthology.org/2023.emnlp-main.507/ | @inproceedings{hao-etal-2023-reasoning,
title = "Reasoning with Language Model is Planning with World Model",
author = "Hao, Shibo and
Gu, Yi and
Ma, Haodi and
Hong, Joshua and
Wang, Zhen and
Wang, Daisy and
Hu, Zhiting",
editor = "Bouamor, Houda and
Pino, Ju... | Large language models (LLMs) have shown remarkable reasoning capabilities, particularly with Chain-of-Thought-style prompts. However, LLMs can still struggle with problems that are easy for humans, such as generating action plans for executing tasks or performing complex math or logical reasoning. This is due to LLMs{'... | [
"Hao, Shibo",
"Gu, Yi",
"Ma, Haodi",
"Hong, Joshua",
"Wang, Zhen",
"Wang, Daisy",
"Hu, Zhiting"
] | Reasoning with Language Model is Planning with World Model | emnlp-main.507 | 2312.05230 | [
"https://github.com/ber666/llm-reasoners"
] | https://huggingface.co/papers/2312.05230 | 0 | 0 | 0 | 2 | [] | [] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.508.bib | https://aclanthology.org/2023.emnlp-main.508/ | @inproceedings{li-etal-2023-llm,
title = "{LLM}-enhanced Self-training for Cross-domain Constituency Parsing",
author = "Li, Jianling and
Zhang, Meishan and
Guo, Peiming and
Zhang, Min and
Zhang, Yue",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
b... | Self-training has proven to be an effective approach for cross-domain tasks, and in this study, we explore its application to cross-domain constituency parsing. Traditional self-training methods rely on limited and potentially low-quality raw corpora. To overcome this limitation, we propose enhancing self-training with... | [
"Li, Jianling",
"Zhang, Meishan",
"Guo, Peiming",
"Zhang, Min",
"Zhang, Yue"
] | LLM-enhanced Self-training for Cross-domain Constituency Parsing | emnlp-main.508 | 2311.02660 | [
"https://github.com/jianlingl/llm_st_constparsing"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.509.bib | https://aclanthology.org/2023.emnlp-main.509/ | @inproceedings{zhang-etal-2023-continual-named,
title = "Continual Named Entity Recognition without Catastrophic Forgetting",
author = "Zhang, Duzhen and
Cong, Wei and
Dong, Jiahua and
Yu, Yahan and
Chen, Xiuyi and
Zhang, Yonggang and
Fang, Zhen",
editor = "Bouamor,... | Continual Named Entity Recognition (CNER) is a burgeoning area, which involves updating an existing model by incorporating new entity types sequentially. Nevertheless, continual learning approaches are often severely afflicted by catastrophic forgetting. This issue is intensified in CNER due to the consolidation of old... | [
"Zhang, Duzhen",
"Cong, Wei",
"Dong, Jiahua",
"Yu, Yahan",
"Chen, Xiuyi",
"Zhang, Yonggang",
"Fang, Zhen"
] | Continual Named Entity Recognition without Catastrophic Forgetting | emnlp-main.509 | 2310.14541 | [
"https://github.com/bladedancer957/cpfd"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.510.bib | https://aclanthology.org/2023.emnlp-main.510/ | @inproceedings{mehta-etal-2023-dsi,
title = "{DSI}++: Updating Transformer Memory with New Documents",
author = "Mehta, Sanket Vaibhav and
Gupta, Jai and
Tay, Yi and
Dehghani, Mostafa and
Tran, Vinh Q. and
Rao, Jinfeng and
Najork, Marc and
Strubell, Emma and
... | Differentiable Search Indices (DSIs) encode a corpus of documents in the parameters of a model and use the same model to map queries directly to relevant document identifiers. Despite the solid performance of DSI models, successfully deploying them in scenarios where document corpora change with time is an open problem... | [
"Mehta, Sanket Vaibhav",
"Gupta, Jai",
"Tay, Yi",
"Dehghani, Mostafa",
"Tran, Vinh Q.",
"Rao, Jinfeng",
"Najork, Marc",
"Strubell, Emma",
"Metzler, Donald"
] | DSI++: Updating Transformer Memory with New Documents | emnlp-main.510 | 2212.09744 | [
""
] | https://huggingface.co/papers/2212.09744 | 0 | 1 | 0 | 9 | [] | [] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.511.bib | https://aclanthology.org/2023.emnlp-main.511/ | @inproceedings{gupta-etal-2023-editing,
title = "Editing Common Sense in Transformers",
author = "Gupta, Anshita and
Mondal, Debanjan and
Sheshadri, Akshay and
Zhao, Wenlong and
Li, Xiang and
Wiegreffe, Sarah and
Tandon, Niket",
editor = "Bouamor, Houda and
P... | Editing model parameters directly in Transformers makes updating open-source transformer-based models possible without re-training. However, these editing methods have only been evaluated on statements about encyclopedic knowledge with a single correct answer. Commonsense knowledge with multiple correct answers, e.g., ... | [
"Gupta, Anshita",
"Mondal, Debanjan",
"Sheshadri, Akshay",
"Zhao, Wenlong",
"Li, Xiang",
"Wiegreffe, Sarah",
"T",
"on, Niket"
] | Editing Common Sense in Transformers | emnlp-main.511 | 2305.14956 | [
"https://github.com/anshitag/memit_csk"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.512.bib | https://aclanthology.org/2023.emnlp-main.512/ | @inproceedings{zhong-etal-2023-air,
title = "Air-Decoding: Attribute Distribution Reconstruction for Decoding-Time Controllable Text Generation",
author = "Zhong, Tianqi and
Wang, Quan and
Han, Jingxuan and
Zhang, Yongdong and
Mao, Zhendong",
editor = "Bouamor, Houda and
P... | Controllable text generation (CTG) aims to generate text with desired attributes, and decoding-time-based methods have shown promising performance on this task. However, in this paper, we identify the phenomenon of Attribute Collapse for the first time. It causes the fluency of generated text to rapidly decrease when t... | [
"Zhong, Tianqi",
"Wang, Quan",
"Han, Jingxuan",
"Zhang, Yongdong",
"Mao, Zhendong"
] | Air-Decoding: Attribute Distribution Reconstruction for Decoding-Time Controllable Text Generation | emnlp-main.512 | 2310.14892 | [
"https://github.com/r1047/air-decoding"
] | https://huggingface.co/papers/2310.14892 | 0 | 1 | 0 | 5 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.513.bib | https://aclanthology.org/2023.emnlp-main.513/ | @inproceedings{mohebbi-etal-2023-homophone,
title = "Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers",
author = "Mohebbi, Hosein and
Chrupa{\l}a, Grzegorz and
Zuidema, Willem and
Alishahi, Afra",
editor = "Bouamor, Houda and
Pino, Juan and
... | Transformers have become a key architecture in speech processing, but our understanding of how they build up representations of acoustic and linguistic structure is limited. In this study, we address this gap by investigating how measures of {`}context-mixing{'} developed for text models can be adapted and applied to m... | [
"Mohebbi, Hosein",
"Chrupa{\\l}a, Grzegorz",
"Zuidema, Willem",
"Alishahi, Afra"
] | Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers | emnlp-main.513 | 2310.09925 | [
"https://github.com/hmohebbi/ContextMixingASR"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.514.bib | https://aclanthology.org/2023.emnlp-main.514/ | @inproceedings{shen-etal-2023-retrieval,
title = "Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System",
author = "Shen, Weizhou and
Gao, Yingqi and
Huang, Canbin and
Wan, Fanqi and
Quan, Xiaojun and
Bi, Wei",
editor = "Bouamor, Houda and
Pino... | Developing an efficient retriever to retrieve knowledge from a large-scale knowledge base (KB) is critical for task-oriented dialogue systems to effectively handle localized and specialized tasks. However, widely used generative models such as T5 and ChatGPT often struggle to differentiate subtle differences among the ... | [
"Shen, Weizhou",
"Gao, Yingqi",
"Huang, Canbin",
"Wan, Fanqi",
"Quan, Xiaojun",
"Bi, Wei"
] | Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System | emnlp-main.514 | 2310.08877 | [
"https://github.com/shenwzh3/mk-tod"
] | https://huggingface.co/papers/2310.08877 | 1 | 0 | 0 | 6 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.515.bib | https://aclanthology.org/2023.emnlp-main.515/ | @inproceedings{yu-etal-2023-ifqa,
title = "{I}f{QA}: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions",
author = "Yu, Wenhao and
Jiang, Meng and
Clark, Peter and
Sabharwal, Ashish",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",... | Although counterfactual reasoning is a fundamental aspect of intelligence, the lack of large-scale counterfactual open-domain question-answering (QA) benchmarks makes it difficult to evaluate and improve models on this ability. To address this void, we introduce the first such dataset, named IfQA, where each question i... | [
"Yu, Wenhao",
"Jiang, Meng",
"Clark, Peter",
"Sabharwal, Ashish"
] | IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions | emnlp-main.515 | 2305.14010 | [
""
] | https://huggingface.co/papers/2305.14010 | 1 | 0 | 0 | 4 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.516.bib | https://aclanthology.org/2023.emnlp-main.516/ | @inproceedings{zhang-etal-2023-large,
title = "How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances",
author = "Zhang, Zihan and
Fang, Meng and
Chen, Ling and
Namazi-Rad, Mohammad-Reza and
Wang, Jun",
editor = "Bouamor, Houda and
... | Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment. Maintaining their up-to-date status is a pressing concern in the current era. This paper provides a comprehensive review of recent advances in aligning deployed LLMs with the ever-changing world... | [
"Zhang, Zihan",
"Fang, Meng",
"Chen, Ling",
"Namazi-Rad, Mohammad-Reza",
"Wang, Jun"
] | How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances | emnlp-main.516 | 2310.07343 | [
"https://github.com/hyintell/awesome-refreshing-llms"
] | https://huggingface.co/papers/2310.07343 | 0 | 0 | 0 | 5 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.517.bib | https://aclanthology.org/2023.emnlp-main.517/ | @inproceedings{han-etal-2023-prewome,
title = "{P}re{W}o{M}e: Exploiting Presuppositions as Working Memory for Long Form Question Answering",
author = "Han, Wookje and
Park, Jinsol and
Lee, Kyungjae",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Pro... | Information-seeking questions in long-form question answering (LFQA) often prove misleading due to ambiguity or false presupposition in the question. While many existing approaches handle misleading questions, they are tailored to limited questions, which are insufficient in a real-world setting with unpredictable inpu... | [
"Han, Wookje",
"Park, Jinsol",
"Lee, Kyungjae"
] | PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering | emnlp-main.517 | 2310.16147 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.518.bib | https://aclanthology.org/2023.emnlp-main.518/ | @inproceedings{dankers-etal-2023-memorisation,
title = "Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation",
author = "Dankers, Verna and
Titov, Ivan and
Hupkes, Dieuwke",
editor = "Bouamor, Houda and
Pino, Juan and
Bali,... | When training a neural network, it will quickly memorise some source-target mappings from your dataset but never learn some others. Yet, memorisation is not easily expressed as a binary feature that is good or bad: individual datapoints lie on a memorisation-generalisation continuum. What determines a datapoint{'}s pos... | [
"Dankers, Verna",
"Titov, Ivan",
"Hupkes, Dieuwke"
] | Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation | emnlp-main.518 | 2311.05379 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.519.bib | https://aclanthology.org/2023.emnlp-main.519/ | @inproceedings{hu-etal-2023-decipherpref,
title = "{D}ecipher{P}ref: Analyzing Influential Factors in Human Preference Judgments via {GPT}-4",
author = "Hu, Yebowen and
Song, Kaiqiang and
Cho, Sangwoo and
Wang, Xiaoyang and
Foroosh, Hassan and
Liu, Fei",
editor = "Bouamor,... | Human preference judgments are pivotal in guiding large language models (LLMs) to produce outputs that align with human values. Human evaluations are also used in summarization tasks to compare outputs from various systems, complementing existing automatic metrics. Despite their significance, however, there has been li... | [
"Hu, Yebowen",
"Song, Kaiqiang",
"Cho, Sangwoo",
"Wang, Xiaoyang",
"Foroosh, Hassan",
"Liu, Fei"
] | DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4 | emnlp-main.519 | 2305.14702 | [
""
] | https://huggingface.co/papers/2305.14702 | 3 | 1 | 0 | 6 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.520.bib | https://aclanthology.org/2023.emnlp-main.520/ | @inproceedings{qiu-etal-2023-gender,
title = "Gender Biases in Automatic Evaluation Metrics for Image Captioning",
author = "Qiu, Haoyi and
Dou, Zi-Yi and
Wang, Tianlu and
Celikyilmaz, Asli and
Peng, Nanyun",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika"... | Model-based evaluation metrics (e.g., CLIPScore and GPTScore) have demonstrated decent correlations with human judgments in various language generation tasks. However, their impact on fairness remains largely unexplored. It is widely recognized that pretrained models can inadvertently encode societal biases, thus emplo... | [
"Qiu, Haoyi",
"Dou, Zi-Yi",
"Wang, Tianlu",
"Celikyilmaz, Asli",
"Peng, Nanyun"
] | Gender Biases in Automatic Evaluation Metrics for Image Captioning | emnlp-main.520 | 2305.14711 | [
"https://github.com/pluslabnlp/clipscore-bias"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.521.bib | https://aclanthology.org/2023.emnlp-main.521/ | @inproceedings{aly-etal-2023-qa,
title = "{QA}-{N}at{V}er: Question Answering for Natural Logic-based Fact Verification",
author = "Aly, Rami and
Strong, Marek and
Vlachos, Andreas",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 20... | Fact verification systems assess a claim{'}s veracity based on evidence. An important consideration in designing them is faithfulness, i.e. generating explanations that accurately reflect the reasoning of the model. Recent works have focused on natural logic, which operates directly on natural language by capturing the... | [
"Aly, Rami",
"Strong, Marek",
"Vlachos, Andreas"
] | QA-NatVer: Question Answering for Natural Logic-based Fact Verification | emnlp-main.521 | 2310.14198 | [
"https://github.com/raldir/qa-natver"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.522.bib | https://aclanthology.org/2023.emnlp-main.522/ | @inproceedings{wiegreffe-etal-2023-increasing,
title = "Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy",
author = "Wiegreffe, Sarah and
Finlayson, Matthew and
Tafjord, Oyvind and
Clark, Peter and
Sabharwal, Ashish",
editor = "Bouamor, Houda and
... | When pretrained language models (LMs) are applied to discriminative tasks such as multiple-choice questions, they place probability mass on vocabulary tokens that aren{'}t among the given answer choices. Spreading probability mass across multiple surface forms with identical meaning (such as {``}bath{''} and {``}bathtu... | [
"Wiegreffe, Sarah",
"Finlayson, Matthew",
"Tafjord, Oyvind",
"Clark, Peter",
"Sabharwal, Ashish"
] | Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy | emnlp-main.522 | 2305.14596 | [
"https://github.com/allenai/revisiting_surface_form_competition"
] | https://huggingface.co/papers/2305.14596 | 1 | 1 | 0 | 5 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.523.bib | https://aclanthology.org/2023.emnlp-main.523/ | @inproceedings{ye-etal-2023-generating,
title = "Generating Data for Symbolic Language with Large Language Models",
author = "Ye, Jiacheng and
Li, Chengzu and
Kong, Lingpeng and
Yu, Tao",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedin... | While large language models (LLMs) bring not only performance but also complexity, recent work has started to turn LLMs into data generators rather than task inferencers, where another affordable task model is trained for efficient deployment and inference. However, such an approach has primarily been applied to natura... | [
"Ye, Jiacheng",
"Li, Chengzu",
"Kong, Lingpeng",
"Yu, Tao"
] | Generating Data for Symbolic Language with Large Language Models | emnlp-main.523 | 2305.13917 | [
"https://github.com/hkunlp/symgen"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.524.bib | https://aclanthology.org/2023.emnlp-main.524/ | @inproceedings{saxena-etal-2023-idtraffickers,
title = "{IDT}raffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements",
author = "Saxena, Vageesh and
Ashpole, Benjamin and
van Dijck, Gijs and
Spanakis, Gerasimos",... | Human trafficking (HT) is a pervasive global issue affecting vulnerable individuals, violating their fundamental human rights. Investigations reveal that a significant number of HT cases are associated with online advertisements (ads), particularly in escort markets. Consequently, identifying and connecting HT vendors ... | [
"Saxena, Vageesh",
"Ashpole, Benjamin",
"van Dijck, Gijs",
"Spanakis, Gerasimos"
] | IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements | emnlp-main.524 | 2310.05484 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.525.bib | https://aclanthology.org/2023.emnlp-main.525/ | @inproceedings{cabello-etal-2023-evaluating,
title = "Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models",
author = "Cabello, Laura and
Bugliarello, Emanuele and
Brandl, Stephanie and
Elliott, Desmond",
editor = "Bouamor, Houda and
Pino, Juan an... | Pretrained machine learning models are known to perpetuate and even amplify existing biases in data, which can result in unfair outcomes that ultimately impact user experience. Therefore, it is crucial to understand the mechanisms behind those prejudicial biases to ensure that model performance does not result in discr... | [
"Cabello, Laura",
"Bugliarello, Emanuele",
"Br",
"l, Stephanie",
"Elliott, Desmond"
] | Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models | emnlp-main.525 | 2310.17530 | [
"https://github.com/coastalcph/gender-neutral-vl"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.526.bib | https://aclanthology.org/2023.emnlp-main.526/ | @inproceedings{fan-etal-2023-improving,
title = "Improving Dialogue Discourse Parsing via Reply-to Structures of Addressee Recognition",
author = "Fan, Yaxin and
Jiang, Feng and
Li, Peifeng and
Kong, Fang and
Zhu, Qiaoming",
editor = "Bouamor, Houda and
Pino, Juan and
... | Dialogue discourse parsing aims to reflect the relation-based structure of dialogue by establishing discourse links according to discourse relations. To alleviate data sparsity, previous studies have adopted multitasking approaches to jointly learn dialogue discourse parsing with related tasks (e.g., reading comprehens... | [
"Fan, Yaxin",
"Jiang, Feng",
"Li, Peifeng",
"Kong, Fang",
"Zhu, Qiaoming"
] | Improving Dialogue Discourse Parsing via Reply-to Structures of Addressee Recognition | emnlp-main.526 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.527.bib | https://aclanthology.org/2023.emnlp-main.527/ | @inproceedings{jang-lukasiewicz-2023-improving,
title = "Improving Language Models{'} Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary",
author = "Jang, Myeongjun and
Lukasiewicz, Thomas",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
b... | The non-humanlike behaviour of contemporary pre-trained language models (PLMs) is a leading cause undermining their trustworthiness. A striking phenomenon of such faulty behaviours is the generation of inconsistent predictions, which produces logically contradictory results, such as generating different predictions for... | [
"Jang, Myeongjun",
"Lukasiewicz, Thomas"
] | Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary | emnlp-main.527 | 2310.15541 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.528.bib | https://aclanthology.org/2023.emnlp-main.528/ | @inproceedings{ghosh-etal-2023-dale,
title = "{DALE}: Generative Data Augmentation for Low-Resource Legal {NLP}",
author = "Ghosh, Sreyan and
Evuru, Chandra Kiran Reddy and
Kumar, Sonal and
Ramaneswaran, S and
Sakshi, S and
Tyagi, Utkarsh and
Manocha, Dinesh",
edito... | We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effective data augmentations of legal documents - legal language, with its specialized vocabulary and complex semantics, morphology, and syntax, ... | [
"Ghosh, Sreyan",
"Evuru, Ch",
"ra Kiran Reddy",
"Kumar, Sonal",
"Ramaneswaran, S",
"Sakshi, S",
"Tyagi, Utkarsh",
"Manocha, Dinesh"
] | DALE: Generative Data Augmentation for Low-Resource Legal NLP | emnlp-main.528 | 2310.15799 | [
"https://github.com/sreyan88/dale"
] | https://huggingface.co/papers/2310.15799 | 3 | 0 | 0 | 7 | [
"ckevuru/DALE"
] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.529.bib | https://aclanthology.org/2023.emnlp-main.529/ | @inproceedings{ma-etal-2023-fedid,
title = "{F}ed{ID}: Federated Interactive Distillation for Large-Scale Pretraining Language Models",
author = "Ma, Xinge and
Liu, Jiangming and
Wang, Jin and
Zhang, Xuejie",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
b... | The growing concerns and regulations surrounding the protection of user data privacy have necessitated decentralized training paradigms. To this end, federated learning (FL) is widely studied in user-related natural language processing (NLP). However, it suffers from several critical limitations including extensive com... | [
"Ma, Xinge",
"Liu, Jiangming",
"Wang, Jin",
"Zhang, Xuejie"
] | FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models | emnlp-main.529 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.530.bib | https://aclanthology.org/2023.emnlp-main.530/ | @inproceedings{havrilla-etal-2023-trlx,
title = "trl{X}: A Framework for Large Scale Reinforcement Learning from Human Feedback",
author = "Havrilla, Alexander and
Zhuravinskyi, Maksym and
Phung, Duy and
Tiwari, Aman and
Tow, Jonathan and
Biderman, Stella and
Anthony, Q... | Reinforcement learning from human feedback (\textbf{RLHF}) utilizes human feedback to better align large language models with human preferences via online optimization against a learned reward model. Current RLHF paradigms rely on Proximal Policy Optimization (\textbf{PPO}), which quickly becomes a challenge to impleme... | [
"Havrilla, Alex",
"er",
"Zhuravinskyi, Maksym",
"Phung, Duy",
"Tiwari, Aman",
"Tow, Jonathan",
"Biderman, Stella",
"Anthony, Quentin",
"Castricato, Louis"
] | trlX: A Framework for Large Scale Reinforcement Learning from Human Feedback | emnlp-main.530 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.531.bib | https://aclanthology.org/2023.emnlp-main.531/ | @inproceedings{garcia-ferrero-etal-2023-dataset,
title = "This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models",
author = "Garc{\'\i}a-Ferrero, Iker and
Altuna, Bego{\~n}a and
Alvez, Javier and
Gonzalez-Dios, Itziar and
Rigau, German",
editor = "Bo... | Although large language models (LLMs) have apparently acquired a certain level of grammatical knowledge and the ability to make generalizations, they fail to interpret negation, a crucial step in Natural Language Processing. We try to clarify the reasons for the sub-optimal performance of LLMs understanding negation. W... | [
"Garc{\\'\\i}a-Ferrero, Iker",
"Altuna, Bego{\\~n}a",
"Alvez, Javier",
"Gonzalez-Dios, Itziar",
"Rigau, German"
] | This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models | emnlp-main.531 | 2310.15941 | [
"https://github.com/hitz-zentroa/this-is-not-a-dataset"
] | https://huggingface.co/papers/2310.15941 | 1 | 6 | 0 | 5 | [] | [
"HiTZ/This-is-not-a-dataset"
] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.532.bib | https://aclanthology.org/2023.emnlp-main.532/ | @inproceedings{li-etal-2023-mt2,
title = "{MT}2: Towards a Multi-Task Machine Translation Model with Translation-Specific In-Context Learning",
author = "Li, Chunyou and
Liu, Mingtong and
Zhang, Hongxiao and
Chen, Yufeng and
Xu, Jinan and
Zhou, Ming",
editor = "Bouamor, Ho... | Sentence-level translation, document-level translation, translation memory, and terminology constrained translation play an important role in machine translation. Most of the previous work uses separate models or methods to solve these tasks, which is not conducive to knowledge transfer of different tasks and increases... | [
"Li, Chunyou",
"Liu, Mingtong",
"Zhang, Hongxiao",
"Chen, Yufeng",
"Xu, Jinan",
"Zhou, Ming"
] | MT2: Towards a Multi-Task Machine Translation Model with Translation-Specific In-Context Learning | emnlp-main.532 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.533.bib | https://aclanthology.org/2023.emnlp-main.533/ | @inproceedings{rucker-akbik-2023-cleanconll,
title = "{C}lean{C}o{NLL}: A Nearly Noise-Free Named Entity Recognition Dataset",
author = {R{\"u}cker, Susanna and
Akbik, Alan},
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference o... | The CoNLL-03 corpus is arguably the most well-known and utilized benchmark dataset for named entity recognition (NER). However, prior works found significant numbers of annotation errors, incompleteness, and inconsistencies in the data. This poses challenges to objectively comparing NER approaches and analyzing their e... | [
"R{\\\"u}cker, Susanna",
"Akbik, Alan"
] | CleanCoNLL: A Nearly Noise-Free Named Entity Recognition Dataset | emnlp-main.533 | 2310.16225 | [
"https://github.com/flairnlp/cleanconll"
] | https://huggingface.co/papers/2310.16225 | 0 | 4 | 2 | 2 | [
"stefan-it/flair-clean-conll-1",
"stefan-it/flair-clean-conll-2",
"stefan-it/flair-clean-conll-3",
"stefan-it/flair-clean-conll-4",
"stefan-it/flair-clean-conll-5"
] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.534.bib | https://aclanthology.org/2023.emnlp-main.534/ | @inproceedings{lim-lauw-2023-disentangling,
title = "Disentangling Transformer Language Models as Superposed Topic Models",
author = "Lim, Jia Peng and
Lauw, Hady",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirica... | Topic Modelling is an established research area where the quality of a given topic is measured using coherence metrics. Often, we infer topics from Neural Topic Models (NTM) by interpreting their decoder weights, consisting of top-activated words projected from individual neurons. Transformer-based Language Models (TLM... | [
"Lim, Jia Peng",
"Lauw, Hady"
] | Disentangling Transformer Language Models as Superposed Topic Models | emnlp-main.534 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.535.bib | https://aclanthology.org/2023.emnlp-main.535/ | @inproceedings{jain-lapata-2023-conversational,
title = "Conversational Semantic Parsing using Dynamic Context Graphs",
author = "Jain, Parag and
Lapata, Mirella",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical... | In this paper we consider the task of conversational semantic parsing over general purpose knowledge graphs (KGs) with millions of entities, and thousands of relation-types. We focus on models which are capable of interactively mapping user utterances into executable logical forms (e.g., Sparql) in the context of the c... | [
"Jain, Parag",
"Lapata, Mirella"
] | Conversational Semantic Parsing using Dynamic Context Graphs | emnlp-main.535 | 2305.06164 | [
"https://github.com/parajain/dynamic_context"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.536.bib | https://aclanthology.org/2023.emnlp-main.536/ | @inproceedings{madusanka-etal-2023-quantifiers,
title = "Not all quantifiers are equal: Probing Transformer-based language models{'} understanding of generalised quantifiers",
author = "Madusanka, Tharindu and
Zahid, Iqra and
Li, Hao and
Pratt-Hartmann, Ian and
Batista-Navarro, Riza"... | How do different generalised quantifiers affect the behaviour of transformer-based language models (TLMs)? The recent popularity of TLMs and the central role generalised quantifiers have traditionally played in linguistics and logic bring this question into particular focus. The current research investigating this subj... | [
"Madusanka, Tharindu",
"Zahid, Iqra",
"Li, Hao",
"Pratt-Hartmann, Ian",
"Batista-Navarro, Riza"
] | Not all quantifiers are equal: Probing Transformer-based language models' understanding of generalised quantifiers | emnlp-main.536 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.537.bib | https://aclanthology.org/2023.emnlp-main.537/ | @inproceedings{zhao-etal-2023-structure,
title = "Structure-aware Knowledge Graph-to-text Generation with Planning Selection and Similarity Distinction",
author = "Zhao, Feng and
Zou, Hongzhi and
Yan, Cheng",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitl... | The knowledge graph-to-text (KG-to-text) generation task aims to synthesize coherent and engaging sentences that accurately convey the complex information derived from an input knowledge graph. One of the primary challenges in this task is bridging the gap between the diverse structures of the KG and the target text, w... | [
"Zhao, Feng",
"Zou, Hongzhi",
"Yan, Cheng"
] | Structure-aware Knowledge Graph-to-text Generation with Planning Selection and Similarity Distinction | emnlp-main.537 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.538.bib | https://aclanthology.org/2023.emnlp-main.538/ | @inproceedings{deng-etal-2023-soul,
title = "{SOUL}: Towards Sentiment and Opinion Understanding of Language",
author = "Deng, Yue and
Zhang, Wenxuan and
Pan, Sinno and
Bing, Lidong",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings o... | Sentiment analysis is a well-established natural language processing task, with sentiment polarity classification being one of its most popular and representative tasks. However, despite the success of pre-trained language models in this area, they often fall short of capturing the broader complexities of sentiment ana... | [
"Deng, Yue",
"Zhang, Wenxuan",
"Pan, Sinno",
"Bing, Lidong"
] | SOUL: Towards Sentiment and Opinion Understanding of Language | emnlp-main.538 | 2310.17924 | [
"https://github.com/damo-nlp-sg/soul"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.539.bib | https://aclanthology.org/2023.emnlp-main.539/ | @inproceedings{goanta-etal-2023-regulation,
title = "Regulation and {NLP} ({R}eg{NLP}): Taming Large Language Models",
author = "Goanta, Catalina and
Aletras, Nikolaos and
Chalkidis, Ilias and
Ranchord{\'a}s, Sofia and
Spanakis, Gerasimos",
editor = "Bouamor, Houda and
Pin... | The scientific innovation in Natural Language Processing (NLP) and more broadly in artificial intelligence (AI) is at its fastest pace to date. As large language models (LLMs) unleash a new era of automation, important debates emerge regarding the benefits and risks of their development, deployment and use. Currently, ... | [
"Goanta, Catalina",
"Aletras, Nikolaos",
"Chalkidis, Ilias",
"Ranchord{\\'a}s, Sofia",
"Spanakis, Gerasimos"
] | Regulation and NLP (RegNLP): Taming Large Language Models | emnlp-main.539 | 2310.05553 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.540.bib | https://aclanthology.org/2023.emnlp-main.540/ | @inproceedings{he-etal-2023-medeval,
title = "{M}ed{E}val: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation",
author = "He, Zexue and
Wang, Yu and
Yan, An and
Liu, Yao and
Chang, Eric and
Gentili, Amilcare and
McAuley, Julian ... | Curated datasets for healthcare are often limited due to the need of human annotations from experts. In this paper, we present MedEval, a multi-level, multi-task, and multi-domain medical benchmark to facilitate the development of language models for healthcare. MedEval is comprehensive and consists of data from severa... | [
"He, Zexue",
"Wang, Yu",
"Yan, An",
"Liu, Yao",
"Chang, Eric",
"Gentili, Amilcare",
"McAuley, Julian",
"Hsu, Chun-Nan"
] | MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation | emnlp-main.540 | 2310.14088 | [
""
] | https://huggingface.co/papers/2310.14088 | 1 | 1 | 0 | 8 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.541.bib | https://aclanthology.org/2023.emnlp-main.541/ | @inproceedings{baumann-etal-2023-seeing,
title = "Seeing through the mess: evolutionary dynamics of lexical polysemy",
author = "Baumann, Andreas and
Stephan, Andreas and
Roth, Benjamin",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of t... | Evidently, words can have multiple senses. For example, the word mess refers to a place to have food or to a confusing situation. How exactly multiple senses emerge is less clear. In this work, we propose and analyze a mathematical model of the evolution of lexical meaning to investigate mechanisms leading to polysemy.... | [
"Baumann, Andreas",
"Stephan, Andreas",
"Roth, Benjamin"
] | Seeing through the mess: evolutionary dynamics of lexical polysemy | emnlp-main.541 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.542.bib | https://aclanthology.org/2023.emnlp-main.542/ | @inproceedings{cheng-etal-2023-embedded,
title = "Are Embedded Potatoes Still Vegetables? On the Limitations of {W}ord{N}et Embeddings for Lexical Semantics",
author = "Cheng, Xuyou and
Schlichtkrull, Michael and
Emerson, Guy",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Ka... | Knowledge Base Embedding (KBE) models have been widely used to encode structured information from knowledge bases, including WordNet. However, the existing literature has predominantly focused on link prediction as the evaluation task, often neglecting exploration of the models{'} semantic capabilities. In this paper, ... | [
"Cheng, Xuyou",
"Schlichtkrull, Michael",
"Emerson, Guy"
] | Are Embedded Potatoes Still Vegetables? On the Limitations of WordNet Embeddings for Lexical Semantics | emnlp-main.542 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.543.bib | https://aclanthology.org/2023.emnlp-main.543/ | @inproceedings{sottana-etal-2023-evaluation,
title = "Evaluation Metrics in the Era of {GPT}-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks",
author = "Sottana, Andrea and
Liang, Bin and
Zou, Kai and
Yuan, Zheng",
editor = "Bouamor, Houda and
Pino, Jua... | Large Language Models (LLMs) evaluation is a patchy and inconsistent landscape, and it is becoming clear that the quality of automatic evaluation metrics is not keeping up with the pace of development of generative models. We aim to improve the understanding of current models{'} performance by providing a preliminary a... | [
"Sottana, Andrea",
"Liang, Bin",
"Zou, Kai",
"Yuan, Zheng"
] | Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks | emnlp-main.543 | 2310.13800 | [
"https://github.com/protagolabs/seq2seq_llm_evaluation"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.544.bib | https://aclanthology.org/2023.emnlp-main.544/ | @inproceedings{wagner-etal-2023-event,
title = "Event-Location Tracking in Narratives: A Case Study on Holocaust Testimonies",
author = "Wagner, Eitan and
Keydar, Renana and
Abend, Omri",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of t... | This work focuses on the spatial dimension of narrative understanding and presents the task of event-location tracking in narrative texts. The task intends to extract the sequence of locations where the narrative is set through its progression. We present several architectures for the task that seeks to model the globa... | [
"Wagner, Eitan",
"Keydar, Renana",
"Abend, Omri"
] | Event-Location Tracking in Narratives: A Case Study on Holocaust Testimonies | emnlp-main.544 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.545.bib | https://aclanthology.org/2023.emnlp-main.545/ | @inproceedings{hwang-etal-2023-dialogizer,
title = "Dialogizer: Context-aware Conversational-{QA} Dataset Generation from Textual Sources",
author = "Hwang, Yerin and
Kim, Yongil and
Bae, Hyunkyung and
Lee, Hwanhee and
Bang, Jeesoo and
Jung, Kyomin",
editor = "Bouamor, Hou... | To address the data scarcity issue in Conversational question answering (ConvQA), a dialog inpainting method, which utilizes documents to generate ConvQA datasets, has been proposed. However, the original dialog inpainting model is trained solely on the dialog reconstruction task, resulting in the generation of questio... | [
"Hwang, Yerin",
"Kim, Yongil",
"Bae, Hyunkyung",
"Lee, Hwanhee",
"Bang, Jeesoo",
"Jung, Kyomin"
] | Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources | emnlp-main.545 | 2311.07589 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.546.bib | https://aclanthology.org/2023.emnlp-main.546/ | @inproceedings{feng-2023-learning,
title = "Learning to Predict Task Transferability via Soft Prompt",
author = "Feng, Lingyun",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
... | Fine-tuning pretrained language models on helpful intermediate tasks often greatly improves the performance of target tasks. However, how to efficiently find the source tasks that can successfully transfer still remains under-explored. In this work, we propose to learn an affinity scoring function to predict transferab... | [
"Feng, Lingyun"
] | Learning to Predict Task Transferability via Soft Prompt | emnlp-main.546 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.547.bib | https://aclanthology.org/2023.emnlp-main.547/ | @inproceedings{zhu-etal-2023-chain,
title = "Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering",
author = "Zhu, Wang and
Thomason, Jesse and
Jia, Robin",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings ... | We propose Chain-of-Questions, a framework that trains a model to robustly answer multistep questions by generating and answering sub-questions. We obtain supervision for sub-questions from human-annotated question decomposition meaning representation (QDMR), but QDMR does not include annotated answers to sub-questions... | [
"Zhu, Wang",
"Thomason, Jesse",
"Jia, Robin"
] | Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering | emnlp-main.547 | 2305.14901 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.548.bib | https://aclanthology.org/2023.emnlp-main.548/ | @inproceedings{zhu-etal-2023-mirror,
title = "Mirror: A Universal Framework for Various Information Extraction Tasks",
author = "Zhu, Tong and
Ren, Junfei and
Yu, Zijian and
Wu, Mengsong and
Zhang, Guoliang and
Qu, Xiaoye and
Chen, Wenliang and
Wang, Zhefeng and... | Sharing knowledge between information extraction tasks has always been a challenge due to the diverse data formats and task variations. Meanwhile, this divergence leads to information waste and increases difficulties in building complex applications in real scenarios. Recent studies often formulate IE tasks as a triple... | [
"Zhu, Tong",
"Ren, Junfei",
"Yu, Zijian",
"Wu, Mengsong",
"Zhang, Guoliang",
"Qu, Xiaoye",
"Chen, Wenliang",
"Wang, Zhefeng",
"Huai, Baoxing",
"Zhang, Min"
] | Mirror: A Universal Framework for Various Information Extraction Tasks | emnlp-main.548 | 2311.05419 | [
"https://github.com/Spico197/Mirror"
] | https://huggingface.co/papers/2311.05419 | 1 | 0 | 0 | 10 | [
"Spico/mirror-chinese-mrcqa-alpha"
] | [] | [
"Spico/Mirror"
] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.549.bib | https://aclanthology.org/2023.emnlp-main.549/ | @inproceedings{handa-etal-2023-mistakes,
title = "{``}Mistakes Help Us Grow{''}: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms",
author = "Handa, Kunal and
Clapper, Margarett and
Boyle, Jessica and
Wang, Rose and
Yang, Diyi and
Yeager, David and... | Teachers{'} growth mindset supportive language (GMSL){---}rhetoric emphasizing that one{'}s skills can be improved over time{---}has been shown to significantly reduce disparities in academic achievement and enhance students{'} learning outcomes. Although teachers espouse growth mindset principles, most find it difficu... | [
"H",
"a, Kunal",
"Clapper, Margarett",
"Boyle, Jessica",
"Wang, Rose",
"Yang, Diyi",
"Yeager, David",
"Demszky, Dorottya"
] | “Mistakes Help Us Grow”: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms | emnlp-main.549 | 2310.10637 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.550.bib | https://aclanthology.org/2023.emnlp-main.550/ | @inproceedings{cao-etal-2023-unnatural,
title = "Unnatural Error Correction: {GPT}-4 Can Almost Perfectly Handle Unnatural Scrambled Text",
author = "Cao, Qi and
Kojima, Takeshi and
Matsuo, Yutaka and
Iwasawa, Yusuke",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kali... | While Large Language Models (LLMs) have achieved remarkable performance in many tasks, much about their inner workings remains unclear. In this study, we present novel experimental insights into the resilience of LLMs, particularly GPT-4, when subjected to extensive character-level permutations. To investigate this, we... | [
"Cao, Qi",
"Kojima, Takeshi",
"Matsuo, Yutaka",
"Iwasawa, Yusuke"
] | Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text | emnlp-main.550 | 2311.18805 | [
"https://github.com/ccqq77/unnatural-error-correction"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.551.bib | https://aclanthology.org/2023.emnlp-main.551/ | @inproceedings{qiu-etal-2023-detecting,
title = "Detecting and Mitigating Hallucinations in Multilingual Summarisation",
author = "Qiu, Yifu and
Ziser, Yftah and
Korhonen, Anna and
Ponti, Edoardo and
Cohen, Shay",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Ka... | Hallucinations pose a significant challenge to the reliability of neural models for abstractive summarisation. While automatically generated summaries may be fluent, they often lack faithfulness to the original document. This issue becomes even more pronounced in low-resource languages, where summarisation requires cro... | [
"Qiu, Yifu",
"Ziser, Yftah",
"Korhonen, Anna",
"Ponti, Edoardo",
"Cohen, Shay"
] | Detecting and Mitigating Hallucinations in Multilingual Summarisation | emnlp-main.551 | 2305.13632 | [
"https://github.com/yfqiu-nlp/mfact-summ"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.552.bib | https://aclanthology.org/2023.emnlp-main.552/ | @inproceedings{kodner-etal-2023-exploring,
title = "Exploring Linguistic Probes for Morphological Generalization",
author = "Kodner, Jordan and
Khalifa, Salam and
Payne, Sarah Ruth Brogden",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings o... | Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supplement that approach with language-specific probes designed to test aspects of morphological generalization. Testing these probes on three m... | [
"Kodner, Jordan",
"Khalifa, Salam",
"Payne, Sarah Ruth Brogden"
] | Exploring Linguistic Probes for Morphological Generalization | emnlp-main.552 | 2310.13686 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.553.bib | https://aclanthology.org/2023.emnlp-main.553/ | @inproceedings{lou-tu-2023-amr,
title = "{AMR} Parsing with Causal Hierarchical Attention and Pointers",
author = "Lou, Chao and
Tu, Kewei",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Lan... | Translation-based AMR parsers have recently gained popularity due to their simplicity and effectiveness. They predict linearized graphs as free texts, avoiding explicit structure modeling. However, this simplicity neglects structural locality in AMR graphs and introduces unnecessary tokens to represent coreferences. In... | [
"Lou, Chao",
"Tu, Kewei"
] | AMR Parsing with Causal Hierarchical Attention and Pointers | emnlp-main.553 | 2310.11964 | [
"https://github.com/louchao98/chap_amr_parser"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.554.bib | https://aclanthology.org/2023.emnlp-main.554/ | @inproceedings{lin-gu-2023-flats,
title = "{FL}at{S}: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score",
author = "Lin, Haowei and
Gu, Yuntian",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conferen... | Detecting out-of-distribution (OOD) instances is crucial for NLP models in practical applications. Although numerous OOD detection methods exist, most of them are empirical. Backed by theoretical analysis, this paper advocates for the measurement of the {``}OOD-ness{''} of a test case $\boldsymbol{x}$ through the \text... | [
"Lin, Haowei",
"Gu, Yuntian"
] | FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score | emnlp-main.554 | 2310.05083 | [
"https://github.com/linhaowei1/flats"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.555.bib | https://aclanthology.org/2023.emnlp-main.555/ | @inproceedings{zheng-etal-2023-self,
title = "Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks",
author = "Zheng, Haoqi and
Zhong, Qihuang and
Ding, Liang and
Tian, Zhiliang and
Niu, Xin and
Wang, Changjian and
Li, Dongs... | Text classification tasks often encounter few-shot scenarios with limited labeled data, and addressing data scarcity is crucial. Data augmentation with mixup merges sample pairs to generate new pseudos, which can relieve the data deficiency issue in text classification. However, the quality of pseudo-samples generated ... | [
"Zheng, Haoqi",
"Zhong, Qihuang",
"Ding, Liang",
"Tian, Zhiliang",
"Niu, Xin",
"Wang, Changjian",
"Li, Dongsheng",
"Tao, Dacheng"
] | Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks | emnlp-main.555 | 2305.13547 | [
""
] | https://huggingface.co/papers/2305.13547 | 1 | 1 | 0 | 7 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.556.bib | https://aclanthology.org/2023.emnlp-main.556/ | @inproceedings{chan-etal-2023-ic3,
title = "{IC}3: Image Captioning by Committee Consensus",
author = "Chan, David and
Myers, Austin and
Vijayanarasimhan, Sudheendra and
Ross, David and
Canny, John",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
boo... | If you ask a human to describe an image, they might do so in a thousand different ways. Traditionally, image captioning models are trained to generate a single {``}best{'} (most like a reference) image caption. Unfortunately, doing so encourages captions that are {``}informationally impoverished,{'} and focus on only a... | [
"Chan, David",
"Myers, Austin",
"Vijayanarasimhan, Sudheendra",
"Ross, David",
"Canny, John"
] | IC3: Image Captioning by Committee Consensus | emnlp-main.556 | 2302.01328 | [
"https://github.com/davidmchan/caption-by-committee"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.557.bib | https://aclanthology.org/2023.emnlp-main.557/ | @inproceedings{manakul-etal-2023-selfcheckgpt,
title = "{S}elf{C}heck{GPT}: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models",
author = "Manakul, Potsawee and
Liusie, Adian and
Gales, Mark",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kal... | Generative Large Language Models (LLMs) such as GPT-3 are capable of generating highly fluent responses to a wide variety of user prompts. However, LLMs are known to hallucinate facts and make non-factual statements which can undermine trust in their output. Existing fact-checking approaches either require access to th... | [
"Manakul, Potsawee",
"Liusie, Adian",
"Gales, Mark"
] | SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models | emnlp-main.557 | 2303.08896 | [
"https://github.com/potsawee/selfcheckgpt"
] | https://huggingface.co/papers/2303.08896 | 1 | 4 | 0 | 3 | [
"potsawee/longformer-large-4096-answerable-squad2",
"bond005/xlm-roberta-xl-hallucination-detector",
"lIlBrother/ko-answerable"
] | [
"potsawee/wiki_bio_gpt3_hallucination"
] | [
"mithril-security/hallucination_detector"
] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.558.bib | https://aclanthology.org/2023.emnlp-main.558/ | @inproceedings{maheshwari-etal-2023-fair,
title = "Fair Without Leveling Down: A New Intersectional Fairness Definition",
author = "Maheshwari, Gaurav and
Bellet, Aur{\'e}lien and
Denis, Pascal and
Keller, Mikaela",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika"... | In this work, we consider the problem of intersectional group fairness in the classification setting, where the objective is to learn discrimination-free models in the presence of several intersecting sensitive groups. First, we illustrate various shortcomings of existing fairness measures commonly used to capture inte... | [
"Maheshwari, Gaurav",
"Bellet, Aur{\\'e}lien",
"Denis, Pascal",
"Keller, Mikaela"
] | Fair Without Leveling Down: A New Intersectional Fairness Definition | emnlp-main.558 | 2305.12495 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.559.bib | https://aclanthology.org/2023.emnlp-main.559/ | @inproceedings{faysse-etal-2023-revisiting,
title = "Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications",
author = "Faysse, Manuel and
Viaud, Gautier and
Hudelot, C{\'e}line and
Colombo, Pierre",
editor = "Bouamor, Houda and
Pino, Juan and
... | Instruction Fine-Tuning (IFT) is a powerful paradigm that strengthens the zero-shot capabilities of Large Language Models (LLMs), but in doing so induces new evaluation metric requirements. We show LLM-based metrics to be well adapted to these requirements, and leverage them to conduct an investigation of task-speciali... | [
"Faysse, Manuel",
"Viaud, Gautier",
"Hudelot, C{\\'e}line",
"Colombo, Pierre"
] | Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications | emnlp-main.559 | 2310.14103 | [
"https://github.com/manuelfay/ifteval"
] | https://huggingface.co/papers/2310.14103 | 1 | 1 | 1 | 4 | [] | [
"manu/IFTEval"
] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.560.bib | https://aclanthology.org/2023.emnlp-main.560/ | @inproceedings{indurthi-etal-2023-clad,
title = "{CLAD}-{ST}: Contrastive Learning with Adversarial Data for Robust Speech Translation",
author = "Indurthi, Sathish and
Chollampatt, Shamil and
Agrawal, Ravi and
Turchi, Marco",
editor = "Bouamor, Houda and
Pino, Juan and
Ba... | The cascaded approach continues to be the most popular choice for speech translation (ST). This approach consists of an automatic speech recognition (ASR) model and a machine translation (MT) model that are used in a pipeline to translate speech in one language to text in another language. MT models are often trained o... | [
"Indurthi, Sathish",
"Chollampatt, Shamil",
"Agrawal, Ravi",
"Turchi, Marco"
] | CLAD-ST: Contrastive Learning with Adversarial Data for Robust Speech Translation | emnlp-main.560 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.561.bib | https://aclanthology.org/2023.emnlp-main.561/ | @inproceedings{zhao-etal-2023-m2df,
title = "{M}2{DF}: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis",
author = "Zhao, Fei and
Li, Chunhui and
Wu, Zhen and
Ouyang, Yawen and
Zhang, Jianbing and
Dai, Xinyu",
editor = "Boua... | Multimodal Aspect-based Sentiment Analysis (MABSA) is a fine-grained Sentiment Analysis task, which has attracted growing research interests recently. Existing work mainly utilizes image information to improve the performance of MABSA task. However, most of the studies overestimate the importance of images since there ... | [
"Zhao, Fei",
"Li, Chunhui",
"Wu, Zhen",
"Ouyang, Yawen",
"Zhang, Jianbing",
"Dai, Xinyu"
] | M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis | emnlp-main.561 | 2310.14605 | [
"https://github.com/grandchicken/m2df"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.562.bib | https://aclanthology.org/2023.emnlp-main.562/ | @inproceedings{chen-etal-2023-detection,
title = "Detection of Multiple Mental Disorders from Social Media with Two-Stream Psychiatric Experts",
author = "Chen, Siyuan and
Zhang, Zhiling and
Wu, Mengyue and
Zhu, Kenny",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kal... | Existing Mental Disease Detection (MDD) research largely studies the detection of a single disorder, overlooking the fact that mental diseases might occur in tandem. Many approaches are not backed by domain knowledge (e.g., psychiatric symptoms) and thus fail to produce interpretable results. To tackle these issues, we... | [
"Chen, Siyuan",
"Zhang, Zhiling",
"Wu, Mengyue",
"Zhu, Kenny"
] | Detection of Multiple Mental Disorders from Social Media with Two-Stream Psychiatric Experts | emnlp-main.562 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.563.bib | https://aclanthology.org/2023.emnlp-main.563/ | @inproceedings{alajrami-etal-2023-understanding,
title = "Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance?",
author = "Alajrami, Ahmed and
Margatina, Katerina and
Aletras, Nikolaos",
editor = "Bouamor, Houda and
Pino, Jua... | Understanding how and what pre-trained language models (PLMs) learn about language is an open challenge in natural language processing. Previous work has focused on identifying whether they capture semantic and syntactic information, and how the data or the pre-training objective affects their performance. However, to ... | [
"Alajrami, Ahmed",
"Margatina, Katerina",
"Aletras, Nikolaos"
] | Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance? | emnlp-main.563 | 2310.17271 | [
""
] | https://huggingface.co/papers/2310.17271 | 0 | 1 | 1 | 3 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.564.bib | https://aclanthology.org/2023.emnlp-main.564/ | @inproceedings{li-etal-2023-improved,
title = "Improved Unsupervised {C}hinese Word Segmentation Using Pre-trained Knowledge and Pseudo-labeling Transfer",
author = "Li, Hsiu-Wen and
Lin, Ying-Jia and
Li, Yi-Ting and
Lin, Chun and
Kao, Hung-Yu",
editor = "Bouamor, Houda and
... | Unsupervised Chinese word segmentation (UCWS) has made progress by incorporating linguistic knowledge from pre-trained language models using parameter-free probing techniques. However, such approaches suffer from increased training time due to the need for multiple inferences using a pre-trained language model to perfo... | [
"Li, Hsiu-Wen",
"Lin, Ying-Jia",
"Li, Yi-Ting",
"Lin, Chun",
"Kao, Hung-Yu"
] | Improved Unsupervised Chinese Word Segmentation Using Pre-trained Knowledge and Pseudo-labeling Transfer | emnlp-main.564 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.565.bib | https://aclanthology.org/2023.emnlp-main.565/ | @inproceedings{tang-etal-2023-easyquant,
title = "{E}asy{Q}uant: An Efficient Data-free Quantization Algorithm for {LLM}s",
author = "Tang, Hanlin and
Sun, Yifu and
Wu, Decheng and
Liu, Kai and
Zhu, Jianchen and
Kang, Zhanhui",
editor = "Bouamor, Houda and
Pino, Jua... | Large language models (LLMs) have proven to be very superior to conventional methods in various tasks. However, their expensive computations and high memory requirements are prohibitive for deployment. Model quantization is an effective method for reducing this overhead. The problem is that in most previous works, the ... | [
"Tang, Hanlin",
"Sun, Yifu",
"Wu, Decheng",
"Liu, Kai",
"Zhu, Jianchen",
"Kang, Zhanhui"
] | EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs | emnlp-main.565 | 2403.02775 | [
""
] | https://huggingface.co/papers/2403.02775 | 1 | 11 | 3 | 6 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.566.bib | https://aclanthology.org/2023.emnlp-main.566/ | @inproceedings{atzeni-etal-2023-polar,
title = "Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings",
author = "Atzeni, Mattia and
Plekhanov, Mikhail and
Dreyer, Frederic and
Kassner, Nora and
Merello, Simone and
Martin, Louis... | Entity linking methods based on dense retrieval are widely adopted in large-scale applications for their efficiency, but they can fall short of generative models, as they are sensitive to the structure of the embedding space. To address this issue, this paper introduces DUCK, an approach to infusing structural informat... | [
"Atzeni, Mattia",
"Plekhanov, Mikhail",
"Dreyer, Frederic",
"Kassner, Nora",
"Merello, Simone",
"Martin, Louis",
"Cancedda, Nicola"
] | Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings | emnlp-main.566 | 2305.12027 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.567.bib | https://aclanthology.org/2023.emnlp-main.567/ | @inproceedings{wang-etal-2023-aprompt,
title = "{AP}rompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models",
author = "Wang, Qifan and
Mao, Yuning and
Wang, Jingang and
Yu, Hanchao and
Nie, Shaoliang and
Wang, Sinong and
Feng, Fuli and
... | With the continuous growth of large language models, the process of fine-tuning these models for new tasks has become increasingly parameter-intensive. Prompt tuning, a method that involves tuning a small set of soft prompts, has emerged as an effective and efficient approach for adapting large pre-trained language mod... | [
"Wang, Qifan",
"Mao, Yuning",
"Wang, Jingang",
"Yu, Hanchao",
"Nie, Shaoliang",
"Wang, Sinong",
"Feng, Fuli",
"Huang, Lifu",
"Quan, Xiaojun",
"Xu, Zenglin",
"Liu, Dongfang"
] | APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models | emnlp-main.567 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.568.bib | https://aclanthology.org/2023.emnlp-main.568/ | @inproceedings{kamath-etal-2023-whats,
title = "What{'}s {``}up{''} with vision-language models? Investigating their struggle with spatial reasoning",
author = "Kamath, Amita and
Hessel, Jack and
Chang, Kai-Wei",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
book... | Recent vision-language (VL) models are powerful, but can they reliably distinguish {``}right{''} from {``}left{''}? We curate three new corpora to quantify model comprehension of such basic spatial relations. These tests isolate spatial reasoning more precisely than existing datasets like VQAv2, e.g., our What{'}sUp be... | [
"Kamath, Amita",
"Hessel, Jack",
"Chang, Kai-Wei"
] | What's “up” with vision-language models? Investigating their struggle with spatial reasoning | emnlp-main.568 | null | [
"https://github.com/amitakamath/whatsup_vlms"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.569.bib | https://aclanthology.org/2023.emnlp-main.569/ | @inproceedings{wang-etal-2023-ibadr,
title = "{IBADR}: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing {NLU} models",
author = "Wang, Xiaoyue and
Liu, Xin and
Wang, Lijie and
Wang, Yaoxiang and
Su, Jinsong and
Wu, Hua",
editor = "Bouamor, Houda and
... | As commonly-used methods for debiasing natural language understanding (NLU) models, dataset refinement approaches heavily rely on manual data analysis, and thus maybe unable to cover all the potential biased features. In this paper, we propose IBADR, an Iterative Bias-Aware Dataset Refinement framework, which debiases ... | [
"Wang, Xiaoyue",
"Liu, Xin",
"Wang, Lijie",
"Wang, Yaoxiang",
"Su, Jinsong",
"Wu, Hua"
] | IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models | emnlp-main.569 | 2311.00292 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.570.bib | https://aclanthology.org/2023.emnlp-main.570/ | @inproceedings{huang-etal-2023-learning-preference,
title = "Learning Preference Model for {LLM}s via Automatic Preference Data Generation",
author = "Huang, Shijia and
Zhao, Jianqiao and
Li, Yanyang and
Wang, Liwei",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalik... | Despite the advanced capacities of the state-of-the-art large language models (LLMs), they suffer from issues of hallucination, stereotype, etc. Preference models play an important role in LLM alignment, yet training preference models predominantly rely on human-annotated data. This reliance limits their versatility an... | [
"Huang, Shijia",
"Zhao, Jianqiao",
"Li, Yanyang",
"Wang, Liwei"
] | Learning Preference Model for LLMs via Automatic Preference Data Generation | emnlp-main.570 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.571.bib | https://aclanthology.org/2023.emnlp-main.571/ | @inproceedings{stap-monz-2023-multilingual,
title = "Multilingual $k$-Nearest-Neighbor Machine Translation",
author = "Stap, David and
Monz, Christof",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in ... | \textit{k}-nearest-neighbor machine translation has demonstrated remarkable improvements in machine translation quality by creating a datastore of cached examples. However, these improvements have been limited to high-resource language pairs, with large datastores, and remain a challenge for low-resource languages. In ... | [
"Stap, David",
"Monz, Christof"
] | Multilingual k-Nearest-Neighbor Machine Translation | emnlp-main.571 | null | [
"https://github.com/davidstap/multilingual-knn-mt"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.572.bib | https://aclanthology.org/2023.emnlp-main.572/ | @inproceedings{miletic-etal-2023-understanding,
title = "Understanding Computational Models of Semantic Change: New Insights from the Speech Community",
author = "Mileti{\'c}, Filip and
Przewozny-Desriaux, Anne and
Tanguy, Ludovic",
editor = "Bouamor, Houda and
Pino, Juan and
Bal... | We investigate the descriptive relevance of widely used semantic change models in linguistic descriptions of present-day speech communities. We focus on the sociolinguistic issue of contact-induced semantic shifts in Quebec English, and analyze 40 target words using type-level and token-level word embeddings, empirical... | [
"Mileti{\\'c}, Filip",
"Przewozny-Desriaux, Anne",
"Tanguy, Ludovic"
] | Understanding Computational Models of Semantic Change: New Insights from the Speech Community | emnlp-main.572 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.573.bib | https://aclanthology.org/2023.emnlp-main.573/ | @inproceedings{nguyen-okazaki-2023-causal,
title = "Causal Reasoning through Two Cognition Layers for Improving Generalization in Visual Question Answering",
author = "Nguyen, Trang and
Okazaki, Naoaki",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceed... | Generalization in Visual Question Answering (VQA) requires models to answer questions about images with contexts beyond the training distribution. Existing attempts primarily refine unimodal aspects, overlooking enhancements in multimodal aspects. Besides, diverse interpretations of the input lead to various modes of a... | [
"Nguyen, Trang",
"Okazaki, Naoaki"
] | Causal Reasoning through Two Cognition Layers for Improving Generalization in Visual Question Answering | emnlp-main.573 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.574.bib | https://aclanthology.org/2023.emnlp-main.574/ | @inproceedings{jiang-etal-2023-structgpt,
title = "{S}truct{GPT}: A General Framework for Large Language Model to Reason over Structured Data",
author = "Jiang, Jinhao and
Zhou, Kun and
Dong, Zican and
Ye, Keming and
Zhao, Xin and
Wen, Ji-Rong",
editor = "Bouamor, Houda a... | In this paper, we aim to improve the reasoning ability of large language models (LLMs) over structured data in a unified way. Inspired by the studies on tool augmentation for LLMs, we develop an Iterative Reading-then-Reasoning (IRR) framework to solve question answering tasks based on structured data, called StructGPT... | [
"Jiang, Jinhao",
"Zhou, Kun",
"Dong, Zican",
"Ye, Keming",
"Zhao, Xin",
"Wen, Ji-Rong"
] | StructGPT: A General Framework for Large Language Model to Reason over Structured Data | emnlp-main.574 | 2305.09645 | [
"https://github.com/rucaibox/structgpt"
] | https://huggingface.co/papers/2305.09645 | 0 | 1 | 0 | 6 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.575.bib | https://aclanthology.org/2023.emnlp-main.575/ | @inproceedings{thalken-etal-2023-modeling,
title = "Modeling Legal Reasoning: {LM} Annotation at the Edge of Human Agreement",
author = "Thalken, Rosamond and
Stiglitz, Edward and
Mimno, David and
Wilkens, Matthew",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika"... | Generative language models (LMs) are increasingly used for document class-prediction tasks and promise enormous improvements in cost and efficiency. Existing research often examines simple classification tasks, but the capability of LMs to classify on complex or specialized tasks is less well understood. We consider a ... | [
"Thalken, Rosamond",
"Stiglitz, Edward",
"Mimno, David",
"Wilkens, Matthew"
] | Modeling Legal Reasoning: LM Annotation at the Edge of Human Agreement | emnlp-main.575 | 2310.18440 | [
"https://github.com/rosthalken/legal-interpretation"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.576.bib | https://aclanthology.org/2023.emnlp-main.576/ | @inproceedings{raman-etal-2023-model,
title = "Model-tuning Via Prompts Makes {NLP} Models Adversarially Robust",
author = "Raman, Mrigank and
Maini, Pratyush and
Kolter, J and
Lipton, Zachary and
Pruthi, Danish",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Ka... | In recent years, NLP practitioners have converged on the following practice: (i) import an off-the-shelf pretrained (masked) language model; (ii) append a multilayer perceptron atop the CLS token{'}s hidden representation (with randomly initialized weights); and (iii) fine-tune the entire model on a downstream task (ML... | [
"Raman, Mrigank",
"Maini, Pratyush",
"Kolter, J",
"Lipton, Zachary",
"Pruthi, Danish"
] | Model-tuning Via Prompts Makes NLP Models Adversarially Robust | emnlp-main.576 | 2303.07320 | [
"https://github.com/acmi-lab/mvp"
] | https://huggingface.co/papers/2303.07320 | 0 | 0 | 0 | 5 | [] | [] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.577.bib | https://aclanthology.org/2023.emnlp-main.577/ | @inproceedings{lee-etal-2023-learning-co,
title = "Learning Co-Speech Gesture for Multimodal Aphasia Type Detection",
author = "Lee, Daeun and
Son, Sejung and
Jeon, Hyolim and
Kim, Seungbae and
Han, Jinyoung",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika... | Aphasia, a language disorder resulting from brain damage, requires accurate identification of specific aphasia types, such as Broca{'}s and Wernicke{'}s aphasia, for effective treatment. However, little attention has been paid to developing methods to detect different types of aphasia. Recognizing the importance of ana... | [
"Lee, Daeun",
"Son, Sejung",
"Jeon, Hyolim",
"Kim, Seungbae",
"Han, Jinyoung"
] | Learning Co-Speech Gesture for Multimodal Aphasia Type Detection | emnlp-main.577 | 2310.11710 | [
"https://github.com/dsail-skku/multimodal-aphasia-type-detection_emnlp_2023"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.578.bib | https://aclanthology.org/2023.emnlp-main.578/ | @inproceedings{li-etal-2023-stinmatch,
title = "{STINM}atch: Semi-Supervised Semantic-Topological Iteration Network for Financial Risk Detection via News Label Diffusion",
author = "Li, Xurui and
Qin, Yue and
Zhu, Rui and
Lin, Tianqianjin and
Fan, Yongming and
Kang, Yangyang ... | Commercial news provide rich semantics and timely information for automated financial risk detection. However, unaffordable large-scale annotation as well as training data sparseness barrier the full exploitation of commercial news in risk detection. To address this problem, we propose a semi-supervised Semantic-Topolo... | [
"Li, Xurui",
"Qin, Yue",
"Zhu, Rui",
"Lin, Tianqianjin",
"Fan, Yongming",
"Kang, Yangyang",
"Song, Kaisong",
"Zhao, Fubang",
"Sun, Changlong",
"Tang, Haixu",
"Liu, Xiaozhong"
] | STINMatch: Semi-Supervised Semantic-Topological Iteration Network for Financial Risk Detection via News Label Diffusion | emnlp-main.578 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.579.bib | https://aclanthology.org/2023.emnlp-main.579/ | @inproceedings{raman-etal-2023-centering,
title = "Centering the Margins: Outlier-Based Identification of Harmed Populations in Toxicity Detection",
author = "Raman, Vyoma and
Fleisig, Eve and
Klein, Dan",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle =... | The impact of AI models on marginalized communities has traditionally been measured by identifying performance differences between specified demographic subgroups. Though this approach aims to center vulnerable groups, it risks obscuring patterns of harm faced by intersectional subgroups or shared across multiple group... | [
"Raman, Vyoma",
"Fleisig, Eve",
"Klein, Dan"
] | Centering the Margins: Outlier-Based Identification of Harmed Populations in Toxicity Detection | emnlp-main.579 | 2305.14735 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.580.bib | https://aclanthology.org/2023.emnlp-main.580/ | @inproceedings{noble-ilinykh-2023-describe,
title = "Describe Me an Auklet: Generating Grounded Perceptual Category Descriptions",
author = "Noble, Bill and
Ilinykh, Nikolai",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference ... | Human speakers can generate descriptions of perceptual concepts, abstracted from the instance-level. Moreover, such descriptions can be used by other speakers to learn provisional representations of those concepts. Learning and using abstract perceptual concepts is under-investigated in the language-and-vision field. T... | [
"Noble, Bill",
"Ilinykh, Nikolai"
] | Describe Me an Auklet: Generating Grounded Perceptual Category Descriptions | emnlp-main.580 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.581.bib | https://aclanthology.org/2023.emnlp-main.581/ | @inproceedings{stammbach-etal-2023-revisiting,
title = "Revisiting Automated Topic Model Evaluation with Large Language Models",
author = "Stammbach, Dominik and
Zouhar, Vil{\'e}m and
Hoyle, Alexander and
Sachan, Mrinmaya and
Ash, Elliott",
editor = "Bouamor, Houda and
Pin... | Topic models help us make sense of large text collections. Automatically evaluating their output and determining the optimal number of topics are both longstanding challenges, with no effective automated solutions to date. This paper proposes using large language models (LLMs) for these tasks. We find that LLMs appropr... | [
"Stammbach, Dominik",
"Zouhar, Vil{\\'e}m",
"Hoyle, Alex",
"er",
"Sachan, Mrinmaya",
"Ash, Elliott"
] | Revisiting Automated Topic Model Evaluation with Large Language Models | emnlp-main.581 | 2305.12152 | [
"https://github.com/dominiksinsaarland/evaluating-topic-model-output"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.582.bib | https://aclanthology.org/2023.emnlp-main.582/ | @inproceedings{zhao-etal-2023-orchid,
title = "{ORCHID}: A {C}hinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarization",
author = "Zhao, Xiutian and
Wang, Ke and
Peng, Wei",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
... | Dialogue agents have been receiving increasing attention for years, and this trend has been further boosted by the recent progress of large language models (LLMs). Stance detection and dialogue summarization are two core tasks of dialogue agents in application scenarios that involve argumentative dialogues. However, re... | [
"Zhao, Xiutian",
"Wang, Ke",
"Peng, Wei"
] | ORCHID: A Chinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarization | emnlp-main.582 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.583.bib | https://aclanthology.org/2023.emnlp-main.583/ | @inproceedings{dikkala-etal-2023-benefits,
title = "On the Benefits of Learning to Route in Mixture-of-Experts Models",
author = "Dikkala, Nishanth and
Ghosh, Nikhil and
Meka, Raghu and
Panigrahy, Rina and
Vyas, Nikhil and
Wang, Xin",
editor = "Bouamor, Houda and
Pi... | Mixture-of-Expert (MoE) Transformer models, such as the Switch Transformer, allow us to successfully scale up model sizes while keeping the amount of compute time fixed. Prior work has established the computational efficiency benefits of using these models. A core component of these models is a router that routes input... | [
"Dikkala, Nishanth",
"Ghosh, Nikhil",
"Meka, Raghu",
"Panigrahy, Rina",
"Vyas, Nikhil",
"Wang, Xin"
] | On the Benefits of Learning to Route in Mixture-of-Experts Models | emnlp-main.583 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.584.bib | https://aclanthology.org/2023.emnlp-main.584/ | @inproceedings{clark-etal-2023-seahorse,
title = "{SEAHORSE}: A Multilingual, Multifaceted Dataset for Summarization Evaluation",
author = "Clark, Elizabeth and
Rijhwani, Shruti and
Gehrmann, Sebastian and
Maynez, Joshua and
Aharoni, Roee and
Nikolaev, Vitaly and
Sellam... | Reliable automatic evaluation of summarization systems is challenging due to the multifaceted and subjective nature of the task. This is especially the case for languages other than English, where human evaluations are scarce. In this work, we introduce SEAHORSE, a dataset for multilingual, multifaceted summarization e... | [
"Clark, Elizabeth",
"Rijhwani, Shruti",
"Gehrmann, Sebastian",
"Maynez, Joshua",
"Aharoni, Roee",
"Nikolaev, Vitaly",
"Sellam, Thibault",
"Siddhant, Aditya",
"Das, Dipanjan",
"Parikh, Ankur"
] | SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation | emnlp-main.584 | 2305.13194 | [
""
] | https://huggingface.co/papers/2305.13194 | 1 | 0 | 0 | 10 | [
"google/seahorse-xxl-q1",
"google/seahorse-xxl-q6",
"google/seahorse-large-q6",
"google/seahorse-xxl-q2",
"google/seahorse-xxl-q5",
"google/seahorse-xxl-q3",
"google/seahorse-xxl-q4",
"google/seahorse-large-q2",
"google/seahorse-large-q1",
"google/seahorse-large-q4",
"google/seahorse-large-q3",
... | [
"tasksource/seahorse_summarization_evaluation"
] | [
"mereojb/google-seahorse-large-q6"
] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.585.bib | https://aclanthology.org/2023.emnlp-main.585/ | @inproceedings{wang-etal-2023-query2doc,
title = "Query2doc: Query Expansion with Large Language Models",
author = "Wang, Liang and
Yang, Nan and
Wei, Furu",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirica... | This paper introduces a simple yet effective query expansion approach, denoted as query2doc, to improve both sparse and dense retrieval systems. The proposed method first generates pseudo-documents by few-shot prompting large language models (LLMs), and then expands the query with generated pseudo documents. LLMs are t... | [
"Wang, Liang",
"Yang, Nan",
"Wei, Furu"
] | Query2doc: Query Expansion with Large Language Models | emnlp-main.585 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.586.bib | https://aclanthology.org/2023.emnlp-main.586/ | @inproceedings{xue-etal-2023-need,
title = "We Need to Talk About Reproducibility in {NLP} Model Comparison",
author = "Xue, Yan and
Cao, Xuefei and
Yang, Xingli and
Wang, Yu and
Wang, Ruibo and
Li, Jihong",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, K... | NLPers frequently face reproducibility crisis in a comparison of various models of a real-world NLP task. Many studies have empirically showed that the standard splits tend to produce low reproducible and unreliable conclusions, and they attempted to improve the splits by using more random repetitions. However, the imp... | [
"Xue, Yan",
"Cao, Xuefei",
"Yang, Xingli",
"Wang, Yu",
"Wang, Ruibo",
"Li, Jihong"
] | We Need to Talk About Reproducibility in NLP Model Comparison | emnlp-main.586 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.587.bib | https://aclanthology.org/2023.emnlp-main.587/ | @inproceedings{wan-etal-2023-explore,
title = "Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration",
author = "Wan, Fanqi and
Huang, Xinting and
Yang, Tao and
Quan, Xiaojun and
Bi, Wei and
Shi, Shuming",
editor = "Bouamor, Houda and... | Instruction-tuning can be substantially optimized through enhanced diversity, resulting in models capable of handling a broader spectrum of tasks. However, existing data employed for such tuning often exhibit an inadequate coverage of individual domains, limiting the scope for nuanced comprehension and interactions wit... | [
"Wan, Fanqi",
"Huang, Xinting",
"Yang, Tao",
"Quan, Xiaojun",
"Bi, Wei",
"Shi, Shuming"
] | Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration | emnlp-main.587 | 2310.09168 | [
"https://github.com/fanqiwan/explore-instruct"
] | https://huggingface.co/papers/2310.09168 | 2 | 2 | 0 | 6 | [
"Wanfq/Explore-LM-Ext-7B-Brainstorming",
"Wanfq/Explore-LM-Ext-7B-Rewriting",
"Wanfq/Explore-LM-7B-Math",
"Wanfq/Explore-LM-7B-Rewriting",
"Wanfq/Explore-LM-Ext-7B-Math",
"Wanfq/Explore-LM-7B-Brainstorming"
] | [
"Wanfq/Explore_Instruct_Brainstorming_16k",
"Wanfq/Explore_Instruct_Rewriting_32k",
"Wanfq/Explore_Instruct_Rewriting_10k",
"Wanfq/Explore_Instruct_Math_10k",
"Wanfq/Explore_Instruct_Math_64k",
"Wanfq/Explore_Instruct_Brainstorming_10k"
] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.588.bib | https://aclanthology.org/2023.emnlp-main.588/ | @inproceedings{irie-etal-2023-practical,
title = "Practical Computational Power of Linear Transformers and Their Recurrent and Self-Referential Extensions",
author = {Irie, Kazuki and
Csord{\'a}s, R{\'o}bert and
Schmidhuber, J{\"u}rgen},
editor = "Bouamor, Houda and
Pino, Juan and
... | Recent studies of the computational power of recurrent neural networks (RNNs) reveal a hierarchy of RNN architectures, given real-time and finite-precision assumptions. Here we study auto-regressive Transformers with linearised attention, a.k.a. linear Transformers (LTs) or Fast Weight Programmers (FWPs). LTs are speci... | [
"Irie, Kazuki",
"Csord{\\'a}s, R{\\'o}bert",
"Schmidhuber, J{\\\"u}rgen"
] | Practical Computational Power of Linear Transformers and Their Recurrent and Self-Referential Extensions | emnlp-main.588 | 2310.16076 | [
"https://github.com/idsia/fwp-formal-lang"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.589.bib | https://aclanthology.org/2023.emnlp-main.589/ | @inproceedings{majumder-etal-2023-interfair,
title = "{I}nter{F}air: Debiasing with Natural Language Feedback for Fair Interpretable Predictions",
author = "Majumder, Bodhisattwa and
He, Zexue and
McAuley, Julian",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
bo... | Debiasing methods in NLP models traditionally focus on isolating information related to a sensitive attribute (e.g., gender or race). We instead argue that a favorable debiasing method should use sensitive information {`}fairly,{'} with explanations, rather than blindly eliminating it. This fair balance is often subjec... | [
"Majumder, Bodhisattwa",
"He, Zexue",
"McAuley, Julian"
] | InterFair: Debiasing with Natural Language Feedback for Fair Interpretable Predictions | emnlp-main.589 | 2210.07440 | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.590.bib | https://aclanthology.org/2023.emnlp-main.590/ | @inproceedings{pu-etal-2023-just,
title = "Just Adjust One Prompt: Enhancing In-Context Dialogue Scoring via Constructing the Optimal Subgraph of Demonstrations and Prompts",
author = "Pu, Jiashu and
Cheng, Ling and
Fan, Lu and
Lv, Tangjie and
Zhang, Rongsheng",
editor = "Bouamor... | The use of modern Large Language Models (LLMs) as chatbots still has some problems such as hallucinations and lack of empathy. Identifying these issues can help improve chatbot performance. The community has been continually iterating on reference-free dialogue evaluation methods based on large language models (LLMs) t... | [
"Pu, Jiashu",
"Cheng, Ling",
"Fan, Lu",
"Lv, Tangjie",
"Zhang, Rongsheng"
] | Just Adjust One Prompt: Enhancing In-Context Dialogue Scoring via Constructing the Optimal Subgraph of Demonstrations and Prompts | emnlp-main.590 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.591.bib | https://aclanthology.org/2023.emnlp-main.591/ | @inproceedings{nikolaev-etal-2023-multilingual,
title = "Multilingual estimation of political-party positioning: From label aggregation to long-input Transformers",
author = "Nikolaev, Dmitry and
Ceron, Tanise and
Pad{\'o}, Sebastian",
editor = "Bouamor, Houda and
Pino, Juan and
... | Scaling analysis is a technique in computational political science that assigns a political actor (e.g. politician or party) a score on a predefined scale based on a (typically long) body of text (e.g. a parliamentary speech or an election manifesto). For example, political scientists have often used the left{--}right ... | [
"Nikolaev, Dmitry",
"Ceron, Tanise",
"Pad{\\'o}, Sebastian"
] | Multilingual estimation of political-party positioning: From label aggregation to long-input Transformers | emnlp-main.591 | 2310.12575 | [
"https://github.com/macleginn/party-positioning-code"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.592.bib | https://aclanthology.org/2023.emnlp-main.592/ | @inproceedings{li-etal-2023-art,
title = "{ART}: rule b{A}sed futu{R}e-inference deduc{T}ion",
author = "Li, Mengze and
Zhao, Tianqi and
Jionghao, Bai and
He, Baoyi and
Miao, Jiaxu and
Ji, Wei and
Lv, Zheqi and
Zhao, Zhou and
Zhang, Shengyu and
Zhan... | Deductive reasoning is a crucial cognitive ability of humanity, allowing us to derive valid conclusions from premises and observations. However, existing works mainly focus on language-based premises and generally neglect deductive reasoning from visual observations. In this work, we introduce rule bAsed futuRe-inferen... | [
"Li, Mengze",
"Zhao, Tianqi",
"Jionghao, Bai",
"He, Baoyi",
"Miao, Jiaxu",
"Ji, Wei",
"Lv, Zheqi",
"Zhao, Zhou",
"Zhang, Shengyu",
"Zhang, Wenqiao",
"Wu, Fei"
] | ART: rule bAsed futuRe-inference deducTion | emnlp-main.592 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.593.bib | https://aclanthology.org/2023.emnlp-main.593/ | @inproceedings{prato-etal-2023-epik,
title = "{E}pi{K}-Eval: Evaluation for Language Models as Epistemic Models",
author = "Prato, Gabriele and
Huang, Jerry and
Parthasarathi, Prasanna and
Sodhani, Shagun and
Chandar, Sarath",
editor = "Bouamor, Houda and
Pino, Juan and
... | In the age of artificial intelligence, the role of large language models (LLMs) is becoming increasingly central. Despite their growing prevalence, their capacity to consolidate knowledge from different training documents{---}a crucial ability in numerous applications{---}remains unexplored. This paper presents the fir... | [
"Prato, Gabriele",
"Huang, Jerry",
"Parthasarathi, Prasanna",
"Sodhani, Shagun",
"Ch",
"ar, Sarath"
] | EpiK-Eval: Evaluation for Language Models as Epistemic Models | emnlp-main.593 | null | [
"https://github.com/chandar-lab/epik-eval"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.594.bib | https://aclanthology.org/2023.emnlp-main.594/ | @inproceedings{xu-etal-2023-dissonance,
title = "From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification",
author = "Xu, Shanshan and
T.y.s.s, Santosh and
Ichim, Oana and
Risini, Isabella and
Plank, Barbara and
Grabmair, ... | In legal NLP, Case Outcome Classification (COC) must not only be accurate but also trustworthy and explainable. Existing work in explainable COC has been limited to annotations by a single expert. However, it is well-known that lawyers may disagree in their assessment of case facts. We hence collect a novel dataset RaV... | [
"Xu, Shanshan",
"T.y.s.s, Santosh",
"Ichim, Oana",
"Risini, Isabella",
"Plank, Barbara",
"Grabmair, Matthias"
] | From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification | emnlp-main.594 | 2310.11878 | [
""
] | https://huggingface.co/papers/2310.11878 | 0 | 0 | 0 | 6 | [] | [
"sxu/RaVE_emnlp23"
] | [] | 1 | Poster |
https://aclanthology.org/2023.emnlp-main.595.bib | https://aclanthology.org/2023.emnlp-main.595/ | @inproceedings{li-etal-2023-bilingual,
title = "On Bilingual Lexicon Induction with Large Language Models",
author = "Li, Yaoyiran and
Korhonen, Anna and
Vuli{\'c}, Ivan",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conferen... | Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations. Inspired by the global paradigm shift in NLP towards Large Language Models (LLMs), we examine the potential of the latest generation of LLMs for the development o... | [
"Li, Yaoyiran",
"Korhonen, Anna",
"Vuli{\\'c}, Ivan"
] | On Bilingual Lexicon Induction with Large Language Models | emnlp-main.595 | null | [
"https://github.com/cambridgeltl/prompt4bli"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.596.bib | https://aclanthology.org/2023.emnlp-main.596/ | @inproceedings{seegmiller-preum-2023-statistical,
title = "Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings",
author = "Seegmiller, Parker and
Preum, Sarah",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the ... | The popularity of transformer-based text embeddings calls for better statistical tools for measuring distributions of such embeddings. One such tool would be a method for ranking texts within a corpus by centrality, i.e. assigning each text a number signifying how representative that text is of the corpus as a whole. H... | [
"Seegmiller, Parker",
"Preum, Sarah"
] | Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings | emnlp-main.596 | 2310.15010 | [
"https://github.com/pkseeg/tte_depth"
] | https://huggingface.co/papers/2310.15010 | 0 | 0 | 0 | 2 | [] | [] | [] | 1 | Oral |
https://aclanthology.org/2023.emnlp-main.597.bib | https://aclanthology.org/2023.emnlp-main.597/ | @inproceedings{zhang-etal-2023-crash,
title = "{CR}a{S}h: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model",
author = "Zhang, Kaiyan and
Ding, Ning and
Qi, Biqing and
Zhu, Xuekai and
Long, Xinwei and
Zhou, Bowen",
editor = "Bouamor, H... | Instruction tuning has recently been recognized as an effective way of aligning Large Language Models (LLMs) to enhance their generalization ability across various tasks. However, when tuning publicly accessible, centralized LLMs with private instruction data, privacy concerns are inevitable. While direct transfer of p... | [
"Zhang, Kaiyan",
"Ding, Ning",
"Qi, Biqing",
"Zhu, Xuekai",
"Long, Xinwei",
"Zhou, Bowen"
] | CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model | emnlp-main.597 | null | [
"https://github.com/tsinghuac3i/crash"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.598.bib | https://aclanthology.org/2023.emnlp-main.598/ | @inproceedings{kumar-etal-2023-multilingual,
title = "From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues",
author = "Kumar, Shivani and
S, Ramaneswaran and
Akhtar, Md and
Chakraborty, Tanmoy",
editor = "Bouamor, Houda an... | Understanding emotions during conversation is a fundamental aspect of human communication, driving NLP research for Emotion Recognition in Conversation (ERC). While considerable research has focused on discerning emotions of individual speakers in monolingual dialogues, understanding the emotional dynamics in code-mixe... | [
"Kumar, Shivani",
"S, Ramaneswaran",
"Akhtar, Md",
"Chakraborty, Tanmoy"
] | From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues | emnlp-main.598 | 2310.13080 | [
"https://github.com/lcs2-iiitd/emnlp-coffee"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Oral | |
https://aclanthology.org/2023.emnlp-main.599.bib | https://aclanthology.org/2023.emnlp-main.599/ | @inproceedings{herrera-berg-etal-2023-large,
title = "Large Language Models are biased to overestimate profoundness",
author = "Herrera-Berg, Eugenio and
Browne, Tom{\'a}s and
Le{\'o}n-Villagr{\'a}, Pablo and
Vives, Marc-Llu{\'\i}s and
Calderon, Cristian",
editor = "Bouamor, Houd... | Recent advancements in natural language processing by large language models (LLMs), such as GPT-4, have been suggested to approach Artificial General Intelligence. And yet, it is still under dispute whether LLMs possess similar reasoning abilities to humans. This study evaluates GPT-4 and various other LLMs in judging ... | [
"Herrera-Berg, Eugenio",
"Browne, Tom{\\'a}s",
"Le{\\'o}n-Villagr{\\'a}, Pablo",
"Vives, Marc-Llu{\\'\\i}s",
"Calderon, Cristian"
] | Large Language Models are biased to overestimate profoundness | emnlp-main.599 | 2310.14422 | [
"https://github.com/ouhenio/llms-overstimate-profoundness"
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster | |
https://aclanthology.org/2023.emnlp-main.600.bib | https://aclanthology.org/2023.emnlp-main.600/ | @inproceedings{laban-etal-2023-summedits,
title = "{S}umm{E}dits: Measuring {LLM} Ability at Factual Reasoning Through The Lens of Summarization",
author = "Laban, Philippe and
Kryscinski, Wojciech and
Agarwal, Divyansh and
Fabbri, Alexander and
Xiong, Caiming and
Joty, Shafiq... | With the recent appearance of LLMs in practical settings, having methods that can effectively detect factual inconsistencies is crucial to reduce the propagation of misinformation and improve trust in model outputs. When testing on existing factual consistency benchmarks, we find that a few large language models (LLMs)... | [
"Laban, Philippe",
"Kryscinski, Wojciech",
"Agarwal, Divyansh",
"Fabbri, Alex",
"er",
"Xiong, Caiming",
"Joty, Shafiq",
"Wu, Chien-Sheng"
] | SummEdits: Measuring LLM Ability at Factual Reasoning Through The Lens of Summarization | emnlp-main.600 | null | [
""
] | -1 | -1 | -1 | -1 | [] | [] | [] | 0 | Poster |
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