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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" ]
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[]
[]
[]
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" ]
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[]
[]
[]
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
[ "" ]
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-1
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[]
[]
[]
0
Poster