paper_id stringlengths 17 19 | title stringlengths 27 144 | paper_url stringlengths 43 45 | authors listlengths 1 37 | abstract large_stringlengths 396 1.69k | anthology_id stringlengths 17 19 | doi stringlengths 29 31 | award stringclasses 0
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2021.emnlp-main.701 | Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors | https://aclanthology.org/2021.emnlp-main.701/ | [
"Marvin Kaster",
"Wei Zhao",
"Steffen Eger"
] | Evaluation metrics are a key ingredient for progress of text generation systems. In recent years, several BERT-based evaluation metrics have been proposed (including BERTScore, MoverScore, BLEURT, etc.) which correlate much better with human assessment of text generation quality than BLEU or ROUGE, invented two decades... | 2021.emnlp-main.701 | 10.18653/v1/2021.emnlp-main.701 | null | 2110.04399 | title_snapshot |
2021.emnlp-main.702 | Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization | https://aclanthology.org/2021.emnlp-main.702/ | [
"Yujian Gan",
"Xinyun Chen",
"Matthew Purver"
] | Recently, there has been significant progress in studying neural networks for translating text descriptions into SQL queries under the zero-shot cross-domain setting. Despite achieving good performance on some public benchmarks, we observe that existing text-to-SQL models do not generalize when facing domain knowledge ... | 2021.emnlp-main.702 | 10.18653/v1/2021.emnlp-main.702 | null | 2109.05157 | title_snapshot |
2021.emnlp-main.703 | What happens if you treat ordinal ratings as interval data? Human evaluations in NLP are even more under-powered than you think | https://aclanthology.org/2021.emnlp-main.703/ | [
"David M. Howcroft",
"Verena Rieser"
] | Previous work has shown that human evaluations in NLP are notoriously under-powered. Here, we argue that there are two common factors which make this problem even worse: NLP studies usually (a) treat ordinal data as interval data and (b) operate under high variance settings while the differences they are hoping to dete... | 2021.emnlp-main.703 | 10.18653/v1/2021.emnlp-main.703 | null | null | null |
2021.emnlp-main.704 | NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender Neutral Alternatives | https://aclanthology.org/2021.emnlp-main.704/ | [
"Eva Vanmassenhove",
"Chris Emmery",
"Dimitar Shterionov"
] | Recent years have seen an increasing need for gender-neutral and inclusive language. Within the field of NLP, there are various mono- and bilingual use cases where gender inclusive language is appropriate, if not preferred due to ambiguity or uncertainty in terms of the gender of referents. In this work, we present a r... | 2021.emnlp-main.704 | 10.18653/v1/2021.emnlp-main.704 | null | 2109.06105 | title_snapshot |
2021.emnlp-main.705 | Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset | https://aclanthology.org/2021.emnlp-main.705/ | [
"Tianqing Fang",
"Weiqi Wang",
"Sehyun Choi",
"Shibo Hao",
"Hongming Zhang",
"Yangqiu Song",
"Bin He"
] | Reasoning over commonsense knowledge bases (CSKB) whose elements are in the form of free-text is an important yet hard task in NLP. While CSKB completion only fills the missing links within the domain of the CSKB, CSKB population is alternatively proposed with the goal of reasoning unseen assertions from external resou... | 2021.emnlp-main.705 | 10.18653/v1/2021.emnlp-main.705 | null | 2109.07679 | title_snapshot |
2021.emnlp-main.706 | Enhancing the Context Representation in Similarity-based Word Sense Disambiguation | https://aclanthology.org/2021.emnlp-main.706/ | [
"Ming Wang",
"Jianzhang Zhang",
"Yinglin Wang"
] | In previous similarity-based WSD systems, studies have allocated much effort on learning comprehensive sense embeddings using contextual representations and knowledge sources. However, the context embedding of an ambiguous word is learned using only the sentence where the word appears, neglecting its global context. In... | 2021.emnlp-main.706 | 10.18653/v1/2021.emnlp-main.706 | null | null | null |
2021.emnlp-main.707 | Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing | https://aclanthology.org/2021.emnlp-main.707/ | [
"Kun Wu",
"Lijie Wang",
"Zhenghua Li",
"Ao Zhang",
"Xinyan Xiao",
"Hua Wu",
"Min Zhang",
"Haifeng Wang"
] | Data augmentation has attracted a lot of research attention in the deep learning era for its ability in alleviating data sparseness. The lack of labeled data for unseen evaluation databases is exactly the major challenge for cross-domain text-to-SQL parsing. Previous works either require human intervention to guarantee... | 2021.emnlp-main.707 | 10.18653/v1/2021.emnlp-main.707 | null | 2103.02227 | title_snapshot |
2021.emnlp-main.708 | SPARQLing Database Queries from Intermediate Question Decompositions | https://aclanthology.org/2021.emnlp-main.708/ | [
"Irina Saparina",
"Anton Osokin"
] | To translate natural language questions into executable database queries, most approaches rely on a fully annotated training set. Annotating a large dataset with queries is difficult as it requires query-language expertise. We reduce this burden using grounded in databases intermediate question representations. These r... | 2021.emnlp-main.708 | 10.18653/v1/2021.emnlp-main.708 | null | 2109.06162 | title_snapshot |
2021.emnlp-main.709 | Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs | https://aclanthology.org/2021.emnlp-main.709/ | [
"Chengjin Xu",
"Fenglong Su",
"Jens Lehmann"
] | Entity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information created the need for reasoning over time in such TKGs. Existing embedding-based entity alignment approaches disregard time information that ... | 2021.emnlp-main.709 | 10.18653/v1/2021.emnlp-main.709 | null | 2203.02150 | title_judge |
2021.emnlp-main.710 | Cross-Domain Label-Adaptive Stance Detection | https://aclanthology.org/2021.emnlp-main.710/ | [
"Momchil Hardalov",
"Arnav Arora",
"Preslav Nakov",
"Isabelle Augenstein"
] | Stance detection concerns the classification of a writer’s viewpoint towards a target. There are different task variants, e.g., stance of a tweet vs. a full article, or stance with respect to a claim vs. an (implicit) topic. Moreover, task definitions vary, which includes the label inventory, the data collection, and t... | 2021.emnlp-main.710 | 10.18653/v1/2021.emnlp-main.710 | null | 2104.07467 | title_snapshot |
2021.emnlp-main.711 | Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification | https://aclanthology.org/2021.emnlp-main.711/ | [
"Shuhuai Ren",
"Jinchao Zhang",
"Lei Li",
"Xu Sun",
"Jie Zhou"
] | Data augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations. Traditional methods first devise task-specific operations such as Synonym Substitute, then preset the corresponding parameters such as the substitution rate artificially, which require... | 2021.emnlp-main.711 | 10.18653/v1/2021.emnlp-main.711 | null | 2109.00523 | title_snapshot |
2021.emnlp-main.712 | Distilling Relation Embeddings from Pretrained Language Models | https://aclanthology.org/2021.emnlp-main.712/ | [
"Asahi Ushio",
"Jose Camacho-Collados",
"Steven Schockaert"
] | Pre-trained language models have been found to capture a surprisingly rich amount of lexical knowledge, ranging from commonsense properties of everyday concepts to detailed factual knowledge about named entities. Among others, this makes it possible to distill high-quality word vectors from pre-trained language models.... | 2021.emnlp-main.712 | 10.18653/v1/2021.emnlp-main.712 | null | null | null |
2021.emnlp-main.713 | Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning | https://aclanthology.org/2021.emnlp-main.713/ | [
"Prasetya Utama",
"Nafise Sadat Moosavi",
"Victor Sanh",
"Iryna Gurevych"
] | Recent prompt-based approaches allow pretrained language models to achieve strong performances on few-shot finetuning by reformulating downstream tasks as a language modeling problem. In this work, we demonstrate that, despite its advantages on low data regimes, finetuned prompt-based models for sentence pair classific... | 2021.emnlp-main.713 | 10.18653/v1/2021.emnlp-main.713 | null | 2109.04144 | title_snapshot |
2021.emnlp-main.714 | A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing | https://aclanthology.org/2021.emnlp-main.714/ | [
"Chunchuan Lyu",
"Shay B. Cohen",
"Ivan Titov"
] | Abstract Meaning Representations (AMR) are a broad-coverage semantic formalism which represents sentence meaning as a directed acyclic graph. To train most AMR parsers, one needs to segment the graph into subgraphs and align each such subgraph to a word in a sentence; this is normally done at preprocessing, relying on ... | 2021.emnlp-main.714 | 10.18653/v1/2021.emnlp-main.714 | null | 2010.12676 | title_snapshot |
2021.emnlp-main.715 | Integrating Personalized PageRank into Neural Word Sense Disambiguation | https://aclanthology.org/2021.emnlp-main.715/ | [
"Ahmed El Sheikh",
"Michele Bevilacqua",
"Roberto Navigli"
] | Neural Word Sense Disambiguation (WSD) has recently been shown to benefit from the incorporation of pre-existing knowledge, such as that coming from the WordNet graph. However, state-of-the-art approaches have been successful in exploiting only the local structure of the graph, with only close neighbors of a given syns... | 2021.emnlp-main.715 | 10.18653/v1/2021.emnlp-main.715 | null | null | null |
2021.emnlp-main.716 | Cross-lingual Sentence Embedding using Multi-Task Learning | https://aclanthology.org/2021.emnlp-main.716/ | [
"Koustava Goswami",
"Sourav Dutta",
"Haytham Assem",
"Theodorus Fransen",
"John P. McCrae"
] | Multilingual sentence embeddings capture rich semantic information not only for measuring similarity between texts but also for catering to a broad range of downstream cross-lingual NLP tasks. State-of-the-art multilingual sentence embedding models require large parallel corpora to learn efficiently, which confines the... | 2021.emnlp-main.716 | 10.18653/v1/2021.emnlp-main.716 | null | null | null |
2021.emnlp-main.717 | NB-MLM: Efficient Domain Adaptation of Masked Language Models for Sentiment Analysis | https://aclanthology.org/2021.emnlp-main.717/ | [
"Nikolay Arefyev",
"Dmitrii Kharchev",
"Artem Shelmanov"
] | While Masked Language Models (MLM) are pre-trained on massive datasets, the additional training with the MLM objective on domain or task-specific data before fine-tuning for the final task is known to improve the final performance. This is usually referred to as the domain or task adaptation step. However, unlike the i... | 2021.emnlp-main.717 | 10.18653/v1/2021.emnlp-main.717 | null | null | null |
2021.emnlp-main.718 | Revisiting Self-training for Few-shot Learning of Language Model | https://aclanthology.org/2021.emnlp-main.718/ | [
"Yiming Chen",
"Yan Zhang",
"Chen Zhang",
"Grandee Lee",
"Ran Cheng",
"Haizhou Li"
] | As unlabeled data carry rich task-relevant information, they are proven useful for few-shot learning of language model. The question is how to effectively make use of such data. In this work, we revisit the self-training technique for language model fine-tuning and present a state-of-the-art prompt-based few-shot learn... | 2021.emnlp-main.718 | 10.18653/v1/2021.emnlp-main.718 | null | 2110.01256 | title_snapshot |
2021.emnlp-main.719 | Bridging Perception, Memory, and Inference through Semantic Relations | https://aclanthology.org/2021.emnlp-main.719/ | [
"Johanna Björklund",
"Adam Dahlgren Lindström",
"Frank Drewes"
] | There is a growing consensus that surface form alone does not enable models to learn meaning and gain language understanding. This warrants an interest in hybrid systems that combine the strengths of neural and symbolic methods. We favour triadic systems consisting of neural networks, knowledge bases, and inference eng... | 2021.emnlp-main.719 | 10.18653/v1/2021.emnlp-main.719 | null | null | null |
2021.emnlp-main.720 | Unimodal and Crossmodal Refinement Network for Multimodal Sequence Fusion | https://aclanthology.org/2021.emnlp-main.720/ | [
"Xiaobao Guo",
"Adams Kong",
"Huan Zhou",
"Xianfeng Wang",
"Min Wang"
] | Effective unimodal representation and complementary crossmodal representation fusion are both important in multimodal representation learning. Prior works often modulate one modal feature to another straightforwardly and thus, underutilizing both unimodal and crossmodal representation refinements, which incurs a bottle... | 2021.emnlp-main.720 | 10.18653/v1/2021.emnlp-main.720 | null | null | null |
2021.emnlp-main.721 | YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews | https://aclanthology.org/2021.emnlp-main.721/ | [
"Matan Orbach",
"Orith Toledo-Ronen",
"Artem Spector",
"Ranit Aharonov",
"Yoav Katz",
"Noam Slonim"
] | Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets. Such an evaluation is limited, and may not reflect true performance on sites like Amazon or Yelp that host diverse reviews from many domains. To address this gap, we present YASO – a new TSA e... | 2021.emnlp-main.721 | 10.18653/v1/2021.emnlp-main.721 | null | 2012.14541 | title_snapshot |
2021.emnlp-main.722 | An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction | https://aclanthology.org/2021.emnlp-main.722/ | [
"Samuel Mensah",
"Kai Sun",
"Nikolaos Aletras"
] | Target-oriented opinion words extraction (TOWE) (Fan et al., 2019b) is a new subtask of target-oriented sentiment analysis that aims to extract opinion words for a given aspect in text. Current state-of-the-art methods leverage position embeddings to capture the relative position of a word to the target. However, the p... | 2021.emnlp-main.722 | 10.18653/v1/2021.emnlp-main.722 | null | 2109.01238 | title_snapshot |
2021.emnlp-main.723 | Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis | https://aclanthology.org/2021.emnlp-main.723/ | [
"Wei Han",
"Hui Chen",
"Soujanya Poria"
] | In multimodal sentiment analysis (MSA), the performance of a model highly depends on the quality of synthesized embeddings. These embeddings are generated from the upstream process called multimodal fusion, which aims to extract and combine the input unimodal raw data to produce a richer multimodal representation. Prev... | 2021.emnlp-main.723 | 10.18653/v1/2021.emnlp-main.723 | null | 2109.00412 | title_snapshot |
2021.emnlp-main.724 | BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification | https://aclanthology.org/2021.emnlp-main.724/ | [
"Zeguan Xiao",
"Jiarun Wu",
"Qingliang Chen",
"Congjian Deng"
] | Graph-based Aspect-based Sentiment Classification (ABSC) approaches have yielded state-of-the-art results, expecially when equipped with contextual word embedding from pre-training language models (PLMs). However, they ignore sequential features of the context and have not yet made the best of PLMs. In this paper, we p... | 2021.emnlp-main.724 | 10.18653/v1/2021.emnlp-main.724 | null | 2110.00171 | title_snapshot |
2021.emnlp-main.725 | Does Social Pressure Drive Persuasion in Online Fora? | https://aclanthology.org/2021.emnlp-main.725/ | [
"Ayush Jain",
"Shashank Srivastava"
] | Online forums such as ChangeMyView have been explored to research aspects of persuasion and argumentative quality in language. While previous research has focused on arguments between a view-holder and a persuader, we explore the premise that apart from the merits of arguments, persuasion is influenced by the ambient s... | 2021.emnlp-main.725 | 10.18653/v1/2021.emnlp-main.725 | null | null | null |
2021.emnlp-main.726 | Aspect Sentiment Quad Prediction as Paraphrase Generation | https://aclanthology.org/2021.emnlp-main.726/ | [
"Wenxuan Zhang",
"Yang Deng",
"Xin Li",
"Yifei Yuan",
"Lidong Bing",
"Wai Lam"
] | Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, aspect term, opinion term, and sentiment polarity. Existing studies usually consider the detection of partial sentiment elements, instead of p... | 2021.emnlp-main.726 | 10.18653/v1/2021.emnlp-main.726 | null | 2110.00796 | title_snapshot |
2021.emnlp-main.727 | Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching | https://aclanthology.org/2021.emnlp-main.727/ | [
"Wenxuan Zhang",
"Ruidan He",
"Haiyun Peng",
"Lidong Bing",
"Wai Lam"
] | Many efforts have been made in solving the Aspect-based sentiment analysis (ABSA) task. While most existing studies focus on English texts, handling ABSA in resource-poor languages remains a challenging problem. In this paper, we consider the unsupervised cross-lingual transfer for the ABSA task, where only labeled dat... | 2021.emnlp-main.727 | 10.18653/v1/2021.emnlp-main.727 | null | null | null |
2021.emnlp-main.728 | Towards Label-Agnostic Emotion Embeddings | https://aclanthology.org/2021.emnlp-main.728/ | [
"Sven Buechel",
"Luise Modersohn",
"Udo Hahn"
] | Research in emotion analysis is scattered across different label formats (e.g., polarity types, basic emotion categories, and affective dimensions), linguistic levels (word vs. sentence vs. discourse), and, of course, (few well-resourced but much more under-resourced) natural languages and text genres (e.g., product re... | 2021.emnlp-main.728 | 10.18653/v1/2021.emnlp-main.728 | null | 2012.00190 | title_snapshot |
2021.emnlp-main.729 | Collaborative Learning of Bidirectional Decoders for Unsupervised Text Style Transfer | https://aclanthology.org/2021.emnlp-main.729/ | [
"Yun Ma",
"Yangbin Chen",
"Xudong Mao",
"Qing Li"
] | Unsupervised text style transfer aims to alter the underlying style of the text to a desired value while keeping its style-independent semantics, without the support of parallel training corpora. Existing methods struggle to achieve both high style conversion rate and low content loss, exhibiting the over-transfer and ... | 2021.emnlp-main.729 | 10.18653/v1/2021.emnlp-main.729 | null | null | null |
2021.emnlp-main.730 | Exploring Non-Autoregressive Text Style Transfer | https://aclanthology.org/2021.emnlp-main.730/ | [
"Yun Ma",
"Qing Li"
] | In this paper, we explore Non-AutoRegressive (NAR) decoding for unsupervised text style transfer. We first propose a base NAR model by directly adapting the common training scheme from its AutoRegressive (AR) counterpart. Despite the faster inference speed over the AR model, this NAR model sacrifices its transfer perfo... | 2021.emnlp-main.730 | 10.18653/v1/2021.emnlp-main.730 | null | null | null |
2021.emnlp-main.731 | PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction | https://aclanthology.org/2021.emnlp-main.731/ | [
"Rajdeep Mukherjee",
"Tapas Nayak",
"Yash Butala",
"Sourangshu Bhattacharya",
"Pawan Goyal"
] | Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinion term/span explaining the rationale behind the sentiment. Existing research efforts are majorly tagging-based. Among the methods taking a s... | 2021.emnlp-main.731 | 10.18653/v1/2021.emnlp-main.731 | null | 2110.04794 | title_snapshot |
2021.emnlp-main.732 | Adaptive Proposal Generation Network for Temporal Sentence Localization in Videos | https://aclanthology.org/2021.emnlp-main.732/ | [
"Daizong Liu",
"Xiaoye Qu",
"Jianfeng Dong",
"Pan Zhou"
] | We address the problem of temporal sentence localization in videos (TSLV). Traditional methods follow a top-down framework which localizes the target segment with pre-defined segment proposals. Although they have achieved decent performance, the proposals are handcrafted and redundant. Recently, bottom-up framework att... | 2021.emnlp-main.732 | 10.18653/v1/2021.emnlp-main.732 | null | 2109.06398 | title_snapshot |
2021.emnlp-main.733 | Progressively Guide to Attend: An Iterative Alignment Framework for Temporal Sentence Grounding | https://aclanthology.org/2021.emnlp-main.733/ | [
"Daizong Liu",
"Xiaoye Qu",
"Pan Zhou"
] | A key solution to temporal sentence grounding (TSG) exists in how to learn effective alignment between vision and language features extracted from an untrimmed video and a sentence description. Existing methods mainly leverage vanilla soft attention to perform the alignment in a single-step process. However, such singl... | 2021.emnlp-main.733 | 10.18653/v1/2021.emnlp-main.733 | null | 2109.06400 | title_snapshot |
2021.emnlp-main.734 | Language Models are Few-Shot Butlers | https://aclanthology.org/2021.emnlp-main.734/ | [
"Vincent Micheli",
"Francois Fleuret"
] | Pretrained language models demonstrate strong performance in most NLP tasks when fine-tuned on small task-specific datasets. Hence, these autoregressive models constitute ideal agents to operate in text-based environments where language understanding and generative capabilities are essential. Nonetheless, collecting ex... | 2021.emnlp-main.734 | 10.18653/v1/2021.emnlp-main.734 | null | 2104.07972 | title_snapshot |
2021.emnlp-main.735 | Rˆ3Net:Relation-embedded Representation Reconstruction Network for Change Captioning | https://aclanthology.org/2021.emnlp-main.735/ | [
"Yunbin Tu",
"Liang Li",
"Chenggang Yan",
"Shengxiang Gao",
"Zhengtao Yu"
] | Change captioning is to use a natural language sentence to describe the fine-grained disagreement between two similar images. Viewpoint change is the most typical distractor in this task, because it changes the scale and location of the objects and overwhelms the representation of real change. In this paper, we propose... | 2021.emnlp-main.735 | 10.18653/v1/2021.emnlp-main.735 | null | 2110.10328 | title_judge |
2021.emnlp-main.736 | Looking for Confirmations: An Effective and Human-Like Visual Dialogue Strategy | https://aclanthology.org/2021.emnlp-main.736/ | [
"Alberto Testoni",
"Raffaella Bernardi"
] | Generating goal-oriented questions in Visual Dialogue tasks is a challenging and longstanding problem. State-Of-The-Art systems are shown to generate questions that, although grammatically correct, often lack an effective strategy and sound unnatural to humans. Inspired by the cognitive literature on information search... | 2021.emnlp-main.736 | 10.18653/v1/2021.emnlp-main.736 | null | 2109.05312 | title_snapshot |
2021.emnlp-main.737 | A Unified Speaker Adaptation Approach for ASR | https://aclanthology.org/2021.emnlp-main.737/ | [
"Yingzhu Zhao",
"Chongjia Ni",
"Cheung-Chi Leung",
"Shafiq Joty",
"Eng Siong Chng",
"Bin Ma"
] | Transformer models have been used in automatic speech recognition (ASR) successfully and yields state-of-the-art results. However, its performance is still affected by speaker mismatch between training and test data. Further finetuning a trained model with target speaker data is the most natural approach for adaptation... | 2021.emnlp-main.737 | 10.18653/v1/2021.emnlp-main.737 | null | 2110.08545 | title_snapshot |
2021.emnlp-main.738 | Caption Enriched Samples for Improving Hateful Memes Detection | https://aclanthology.org/2021.emnlp-main.738/ | [
"Efrat Blaier",
"Itzik Malkiel",
"Lior Wolf"
] | The recently introduced hateful meme challenge demonstrates the difficulty of determining whether a meme is hateful or not. Specifically, both unimodal language models and multimodal vision-language models cannot reach the human level of performance. Motivated by the need to model the contrast between the image content... | 2021.emnlp-main.738 | 10.18653/v1/2021.emnlp-main.738 | null | 2109.10649 | title_snapshot |
2021.emnlp-main.739 | Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems | https://aclanthology.org/2021.emnlp-main.739/ | [
"Potsawee Manakul",
"Mark Gales"
] | Transformer models have achieved state-of-the-art results in a wide range of NLP tasks including summarization. Training and inference using large transformer models can be computationally expensive. Previous work has focused on one important bottleneck, the quadratic self-attention mechanism in the encoder. Modified e... | 2021.emnlp-main.739 | 10.18653/v1/2021.emnlp-main.739 | null | 2109.03888 | title_snapshot |
2021.emnlp-main.740 | BARThez: a Skilled Pretrained French Sequence-to-Sequence Model | https://aclanthology.org/2021.emnlp-main.740/ | [
"Moussa Kamal Eddine",
"Antoine Tixier",
"Michalis Vazirgiannis"
] | Inductive transfer learning has taken the entire NLP field by storm, with models such as BERT and BART setting new state of the art on countless NLU tasks. However, most of the available models and research have been conducted for English. In this work, we introduce BARThez, the first large-scale pretrained seq2seq mod... | 2021.emnlp-main.740 | 10.18653/v1/2021.emnlp-main.740 | null | 2010.12321 | title_snapshot |
2021.emnlp-main.741 | ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization | https://aclanthology.org/2021.emnlp-main.741/ | [
"Alireza Salemi",
"Emad Kebriaei",
"Ghazal Neisi Minaei",
"Azadeh Shakery"
] | Abstractive text summarization is one of the areas influenced by the emergence of pre-trained language models. Current pre-training works in abstractive summarization give more points to the summaries with more words in common with the main text and pay less attention to the semantic similarity between generated senten... | 2021.emnlp-main.741 | 10.18653/v1/2021.emnlp-main.741 | null | 2109.04098 | title_snapshot |
2021.emnlp-main.742 | Models and Datasets for Cross-Lingual Summarisation | https://aclanthology.org/2021.emnlp-main.742/ | [
"Laura Perez-Beltrachini",
"Mirella Lapata"
] | We present a cross-lingual summarisation corpus with long documents in a source language associated with multi-sentence summaries in a target language. The corpus covers twelve language pairs and directions for four European languages, namely Czech, English, French and German, and the methodology for its creation can b... | 2021.emnlp-main.742 | 10.18653/v1/2021.emnlp-main.742 | null | 2202.09583 | title_snapshot |
2021.emnlp-main.743 | Learning Opinion Summarizers by Selecting Informative Reviews | https://aclanthology.org/2021.emnlp-main.743/ | [
"Arthur Bražinskas",
"Mirella Lapata",
"Ivan Titov"
] | Opinion summarization has been traditionally approached with unsupervised, weakly-supervised and few-shot learning techniques. In this work, we collect a large dataset of summaries paired with user reviews for over 31,000 products, enabling supervised training. However, the number of reviews per product is large (320 o... | 2021.emnlp-main.743 | 10.18653/v1/2021.emnlp-main.743 | null | 2109.04325 | title_snapshot |
2021.emnlp-main.744 | Enriching and Controlling Global Semantics for Text Summarization | https://aclanthology.org/2021.emnlp-main.744/ | [
"Thong Nguyen",
"Anh Tuan Luu",
"Truc Lu",
"Tho Quan"
] | Recently, Transformer-based models have been proven effective in the abstractive summarization task by creating fluent and informative summaries. Nevertheless, these models still suffer from the short-range dependency problem, causing them to produce summaries that miss the key points of document. In this paper, we att... | 2021.emnlp-main.744 | 10.18653/v1/2021.emnlp-main.744 | null | 2109.10616 | title_snapshot |
2021.emnlp-main.745 | Revisiting Tri-training of Dependency Parsers | https://aclanthology.org/2021.emnlp-main.745/ | [
"Joachim Wagner",
"Jennifer Foster"
] | We compare two orthogonal semi-supervised learning techniques, namely tri-training and pretrained word embeddings, in the task of dependency parsing. We explore language-specific FastText and ELMo embeddings and multilingual BERT embeddings. We focus on a low resource scenario as semi-supervised learning can be expecte... | 2021.emnlp-main.745 | 10.18653/v1/2021.emnlp-main.745 | null | 2109.08122 | title_snapshot |
2021.emnlp-main.746 | Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling | https://aclanthology.org/2021.emnlp-main.746/ | [
"Liwen Wang",
"Xuefeng Li",
"Jiachi Liu",
"Keqing He",
"Yuanmeng Yan",
"Weiran Xu"
] | Zero-shot cross-domain slot filling alleviates the data dependence in the case of data scarcity in the target domain, which has aroused extensive research. However, as most of the existing methods do not achieve effective knowledge transfer to the target domain, they just fit the distribution of the seen slot and show ... | 2021.emnlp-main.746 | 10.18653/v1/2021.emnlp-main.746 | null | 2110.03572 | title_snapshot |
2021.emnlp-main.747 | Neuralizing Regular Expressions for Slot Filling | https://aclanthology.org/2021.emnlp-main.747/ | [
"Chengyue Jiang",
"Zijian Jin",
"Kewei Tu"
] | Neural models and symbolic rules such as regular expressions have their respective merits and weaknesses. In this paper, we study the integration of the two approaches for the slot filling task by converting regular expressions into neural networks. Specifically, we first convert regular expressions into a special form... | 2021.emnlp-main.747 | 10.18653/v1/2021.emnlp-main.747 | null | null | null |
2021.emnlp-main.748 | Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP | https://aclanthology.org/2021.emnlp-main.748/ | [
"Zhijing Jin",
"Julius von Kügelgen",
"Jingwei Ni",
"Tejas Vaidhya",
"Ayush Kaushal",
"Mrinmaya Sachan",
"Bernhard Schölkopf"
] | The principle of independent causal mechanisms (ICM) states that generative processes of real world data consist of independent modules which do not influence or inform each other. While this idea has led to fruitful developments in the field of causal inference, it is not widely-known in the NLP community. In this wor... | 2021.emnlp-main.748 | 10.18653/v1/2021.emnlp-main.748 | null | 2110.03618 | title_snapshot |
2021.emnlp-main.749 | Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning | https://aclanthology.org/2021.emnlp-main.749/ | [
"Runxin Xu",
"Fuli Luo",
"Zhiyuan Zhang",
"Chuanqi Tan",
"Baobao Chang",
"Songfang Huang",
"Fei Huang"
] | Recent pretrained language models extend from millions to billions of parameters. Thus the need to fine-tune an extremely large pretrained model with a limited training corpus arises in various downstream tasks. In this paper, we propose a straightforward yet effective fine-tuning technique, Child-Tuning, which updates... | 2021.emnlp-main.749 | 10.18653/v1/2021.emnlp-main.749 | null | 2109.05687 | title_snapshot |
2021.emnlp-main.750 | Knowledge Graph Representation Learning using Ordinary Differential Equations | https://aclanthology.org/2021.emnlp-main.750/ | [
"Mojtaba Nayyeri",
"Chengjin Xu",
"Franca Hoffmann",
"Mirza Mohtashim Alam",
"Jens Lehmann",
"Sahar Vahdati"
] | Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a knowledge graph into a geometric space. The capability of KGEs in preserving graph characteristics including structural aspects and semantics, highly depends on the design of their sc... | 2021.emnlp-main.750 | 10.18653/v1/2021.emnlp-main.750 | null | null | null |
2021.emnlp-main.751 | KnowMAN: Weakly Supervised Multinomial Adversarial Networks | https://aclanthology.org/2021.emnlp-main.751/ | [
"Luisa März",
"Ehsaneddin Asgari",
"Fabienne Braune",
"Franziska Zimmermann",
"Benjamin Roth"
] | The absence of labeled data for training neural models is often addressed by leveraging knowledge about the specific task, resulting in heuristic but noisy labels. The knowledge is captured in labeling functions, which detect certain regularities or patterns in the training samples and annotate corresponding labels for... | 2021.emnlp-main.751 | 10.18653/v1/2021.emnlp-main.751 | null | 2109.07994 | title_snapshot |
2021.emnlp-main.752 | ONION: A Simple and Effective Defense Against Textual Backdoor Attacks | https://aclanthology.org/2021.emnlp-main.752/ | [
"Fanchao Qi",
"Yangyi Chen",
"Mukai Li",
"Yuan Yao",
"Zhiyuan Liu",
"Maosong Sun"
] | Backdoor attacks are a kind of emergent training-time threat to deep neural networks (DNNs). They can manipulate the output of DNNs and possess high insidiousness. In the field of natural language processing, some attack methods have been proposed and achieve very high attack success rates on multiple popular models. N... | 2021.emnlp-main.752 | 10.18653/v1/2021.emnlp-main.752 | null | 2011.10369 | title_snapshot |
2021.emnlp-main.753 | Value-aware Approximate Attention | https://aclanthology.org/2021.emnlp-main.753/ | [
"Ankit Gupta",
"Jonathan Berant"
] | Following the success of dot-product attention in Transformers, numerous approximations have been recently proposed to address its quadratic complexity with respect to the input length. However, all approximations thus far have ignored the contribution of the *value vectors* to the quality of approximation. In this wor... | 2021.emnlp-main.753 | 10.18653/v1/2021.emnlp-main.753 | null | 2103.09857 | title_snapshot |
2021.emnlp-main.754 | Contrastive Domain Adaptation for Question Answering using Limited Text Corpora | https://aclanthology.org/2021.emnlp-main.754/ | [
"Zhenrui Yue",
"Bernhard Kratzwald",
"Stefan Feuerriegel"
] | Question generation has recently shown impressive results in customizing question answering (QA) systems to new domains. These approaches circumvent the need for manually annotated training data from the new domain and, instead, generate synthetic question-answer pairs that are used for training. However, existing meth... | 2021.emnlp-main.754 | 10.18653/v1/2021.emnlp-main.754 | null | 2108.13854 | title_snapshot |
2021.emnlp-main.755 | Case-based Reasoning for Natural Language Queries over Knowledge Bases | https://aclanthology.org/2021.emnlp-main.755/ | [
"Rajarshi Das",
"Manzil Zaheer",
"Dung Thai",
"Ameya Godbole",
"Ethan Perez",
"Jay Yoon Lee",
"Lizhen Tan",
"Lazaros Polymenakos",
"Andrew McCallum"
] | It is often challenging to solve a complex problem from scratch, but much easier if we can access other similar problems with their solutions — a paradigm known as case-based reasoning (CBR). We propose a neuro-symbolic CBR approach (CBR-KBQA) for question answering over large knowledge bases. CBR-KBQA consists of a no... | 2021.emnlp-main.755 | 10.18653/v1/2021.emnlp-main.755 | null | 2104.08762 | title_snapshot |
2021.emnlp-main.756 | Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation | https://aclanthology.org/2021.emnlp-main.756/ | [
"Chen Zhao",
"Chenyan Xiong",
"Jordan Boyd-Graber",
"Hal Daumé III"
] | Open-domain question answering answers a question based on evidence retrieved from a large corpus. State-of-the-art neural approaches require intermediate evidence annotations for training. However, such intermediate annotations are expensive, and methods that rely on them cannot transfer to the more common setting, wh... | 2021.emnlp-main.756 | 10.18653/v1/2021.emnlp-main.756 | null | 2110.04889 | title_judge |
2021.emnlp-main.757 | What’s in a Name? Answer Equivalence For Open-Domain Question Answering | https://aclanthology.org/2021.emnlp-main.757/ | [
"Chenglei Si",
"Chen Zhao",
"Jordan Boyd-Graber"
] | A flaw in QA evaluation is that annotations often only provide one gold answer. Thus, model predictions semantically equivalent to the answer but superficially different are considered incorrect. This work explores mining alias entities from knowledge bases and using them as additional gold answers (i.e., equivalent an... | 2021.emnlp-main.757 | 10.18653/v1/2021.emnlp-main.757 | null | 2109.05289 | title_snapshot |
2021.emnlp-main.758 | Evaluation Paradigms in Question Answering | https://aclanthology.org/2021.emnlp-main.758/ | [
"Pedro Rodriguez",
"Jordan Boyd-Graber"
] | Question answering (QA) primarily descends from two branches of research: (1) Alan Turing’s investigation of machine intelligence at Manchester University and (2) Cyril Cleverdon’s comparison of library card catalog indices at Cranfield University. This position paper names and distinguishes these paradigms. Despite su... | 2021.emnlp-main.758 | 10.18653/v1/2021.emnlp-main.758 | null | null | null |
2021.emnlp-main.759 | Numerical reasoning in machine reading comprehension tasks: are we there yet? | https://aclanthology.org/2021.emnlp-main.759/ | [
"Hadeel Al-Negheimish",
"Pranava Madhyastha",
"Alessandra Russo"
] | Numerical reasoning based machine reading comprehension is a task that involves reading comprehension along with using arithmetic operations such as addition, subtraction, sorting and counting. The DROP benchmark (Dua et al., 2019) is a recent dataset that has inspired the design of NLP models aimed at solving this tas... | 2021.emnlp-main.759 | 10.18653/v1/2021.emnlp-main.759 | null | 2109.08207 | title_snapshot |
2021.emnlp-main.760 | Set Generation Networks for End-to-End Knowledge Base Population | https://aclanthology.org/2021.emnlp-main.760/ | [
"Dianbo Sui",
"Chenhao Wang",
"Yubo Chen",
"Kang Liu",
"Jun Zhao",
"Wei Bi"
] | The task of knowledge base population (KBP) aims to discover facts about entities from texts and expand a knowledge base with these facts. Previous studies shape end-to-end KBP as a machine translation task, which is required to convert unordered fact into a sequence according to a pre-specified order. However, the fac... | 2021.emnlp-main.760 | 10.18653/v1/2021.emnlp-main.760 | null | null | null |
2021.emnlp-main.761 | Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction | https://aclanthology.org/2021.emnlp-main.761/ | [
"Kailong Hao",
"Botao Yu",
"Wei Hu"
] | Distantly supervised relation extraction (RE) automatically aligns unstructured text with relation instances in a knowledge base (KB). Due to the incompleteness of current KBs, sentences implying certain relations may be annotated as N/A instances, which causes the so-called false negative (FN) problem. Current RE meth... | 2021.emnlp-main.761 | 10.18653/v1/2021.emnlp-main.761 | null | 2109.02099 | title_snapshot |
2021.emnlp-main.762 | Progressive Adversarial Learning for Bootstrapping: A Case Study on Entity Set Expansion | https://aclanthology.org/2021.emnlp-main.762/ | [
"Lingyong Yan",
"Xianpei Han",
"Le Sun"
] | Bootstrapping has become the mainstream method for entity set expansion. Conventional bootstrapping methods mostly define the expansion boundary using seed-based distance metrics, which heavily depend on the quality of selected seeds and are hard to be adjusted due to the extremely sparse supervision. In this paper, we... | 2021.emnlp-main.762 | 10.18653/v1/2021.emnlp-main.762 | null | 2109.12082 | title_snapshot |
2021.emnlp-main.763 | Uncovering Main Causalities for Long-tailed Information Extraction | https://aclanthology.org/2021.emnlp-main.763/ | [
"Guoshun Nan",
"Jiaqi Zeng",
"Rui Qiao",
"Zhijiang Guo",
"Wei Lu"
] | Information Extraction (IE) aims to extract structural information from unstructured texts. In practice, long-tailed distributions caused by the selection bias of a dataset may lead to incorrect correlations, also known as spurious correlations, between entities and labels in the conventional likelihood models. This mo... | 2021.emnlp-main.763 | 10.18653/v1/2021.emnlp-main.763 | null | 2109.05213 | title_snapshot |
2021.emnlp-main.764 | Maximal Clique Based Non-Autoregressive Open Information Extraction | https://aclanthology.org/2021.emnlp-main.764/ | [
"Bowen Yu",
"Yucheng Wang",
"Tingwen Liu",
"Hongsong Zhu",
"Limin Sun",
"Bin Wang"
] | Open Information Extraction (OpenIE) aims to discover textual facts from a given sentence. In essence, the facts contained in plain text are unordered. However, the popular OpenIE systems usually output facts sequentially in the way of predicting the next fact conditioned on the previous decoded ones, which enforce an ... | 2021.emnlp-main.764 | 10.18653/v1/2021.emnlp-main.764 | null | null | null |
2021.emnlp-main.765 | A Relation-Oriented Clustering Method for Open Relation Extraction | https://aclanthology.org/2021.emnlp-main.765/ | [
"Jun Zhao",
"Tao Gui",
"Qi Zhang",
"Yaqian Zhou"
] | The clustering-based unsupervised relation discovery method has gradually become one of the important methods of open relation extraction (OpenRE). However, high-dimensional vectors can encode complex linguistic information which leads to the problem that the derived clusters cannot explicitly align with the relational... | 2021.emnlp-main.765 | 10.18653/v1/2021.emnlp-main.765 | null | 2109.07205 | title_snapshot |
2021.emnlp-main.766 | Exploring Methods for Generating Feedback Comments for Writing Learning | https://aclanthology.org/2021.emnlp-main.766/ | [
"Kazuaki Hanawa",
"Ryo Nagata",
"Kentaro Inui"
] | The task of generating explanatory notes for language learners is known as feedback comment generation. Although various generation techniques are available, little is known about which methods are appropriate for this task. Nagata (2019) demonstrates the effectiveness of neural-retrieval-based methods in generating fe... | 2021.emnlp-main.766 | 10.18653/v1/2021.emnlp-main.766 | null | null | null |
2021.emnlp-main.767 | A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis | https://aclanthology.org/2021.emnlp-main.767/ | [
"Jiawei Liu",
"Kaisong Song",
"Yangyang Kang",
"Guoxiu He",
"Zhuoren Jiang",
"Changlong Sun",
"Wei Lu",
"Xiaozhong Liu"
] | Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension. Recently, Machine-Human Chatting Handoff (MHCH), predicting chatbot failure and enabling human-algorithm collaboration to enhance ch... | 2021.emnlp-main.767 | 10.18653/v1/2021.emnlp-main.767 | null | 2109.08412 | title_snapshot |
2021.emnlp-main.768 | Meta Distant Transfer Learning for Pre-trained Language Models | https://aclanthology.org/2021.emnlp-main.768/ | [
"Chengyu Wang",
"Haojie Pan",
"Minghui Qiu",
"Jun Huang",
"Fei Yang",
"Yin Zhang"
] | With the wide availability of Pre-trained Language Models (PLMs), multi-task fine-tuning across domains has been extensively applied. For tasks related to distant domains with different class label sets, PLMs may memorize non-transferable knowledge for the target domain and suffer from negative transfer. Inspired by me... | 2021.emnlp-main.768 | 10.18653/v1/2021.emnlp-main.768 | null | null | null |
2021.emnlp-main.769 | UniKER: A Unified Framework for Combining Embedding and Definite Horn Rule Reasoning for Knowledge Graph Inference | https://aclanthology.org/2021.emnlp-main.769/ | [
"Kewei Cheng",
"Ziqing Yang",
"Ming Zhang",
"Yizhou Sun"
] | Knowledge graph inference has been studied extensively due to its wide applications. It has been addressed by two lines of research, i.e., the more traditional logical rule reasoning and the more recent knowledge graph embedding (KGE). Several attempts have been made to combine KGE and logical rules for better knowledg... | 2021.emnlp-main.769 | 10.18653/v1/2021.emnlp-main.769 | null | null | null |
2021.emnlp-main.770 | Wasserstein Selective Transfer Learning for Cross-domain Text Mining | https://aclanthology.org/2021.emnlp-main.770/ | [
"Lingyun Feng",
"Minghui Qiu",
"Yaliang Li",
"Haitao Zheng",
"Ying Shen"
] | Transfer learning (TL) seeks to improve the learning of a data-scarce target domain by using information from source domains. However, the source and target domains usually have different data distributions, which may lead to negative transfer. To alleviate this issue, we propose a Wasserstein Selective Transfer Learni... | 2021.emnlp-main.770 | 10.18653/v1/2021.emnlp-main.770 | null | null | null |
2021.emnlp-main.771 | Jointly Learning to Repair Code and Generate Commit Message | https://aclanthology.org/2021.emnlp-main.771/ | [
"Jiaqi Bai",
"Long Zhou",
"Ambrosio Blanco",
"Shujie Liu",
"Furu Wei",
"Ming Zhou",
"Zhoujun Li"
] | We propose a novel task of jointly repairing program codes and generating commit messages. Code repair and commit message generation are two essential and related tasks for software development. However, existing work usually performs the two tasks independently. We construct a multilingual triple dataset including bug... | 2021.emnlp-main.771 | 10.18653/v1/2021.emnlp-main.771 | null | 2109.12296 | title_snapshot |
2021.emnlp-main.772 | Inflate and Shrink:Enriching and Reducing Interactions for Fast Text-Image Retrieval | https://aclanthology.org/2021.emnlp-main.772/ | [
"Haoliang Liu",
"Tan Yu",
"Ping Li"
] | By exploiting the cross-modal attention, cross-BERT methods have achieved state-of-the-art accuracy in cross-modal retrieval. Nevertheless, the heavy text-image interactions in the cross-BERT model are prohibitively slow for large-scale retrieval. Late-interaction methods trade off retrieval accuracy and efficiency by ... | 2021.emnlp-main.772 | 10.18653/v1/2021.emnlp-main.772 | null | null | null |
2021.emnlp-main.773 | On Pursuit of Designing Multi-modal Transformer for Video Grounding | https://aclanthology.org/2021.emnlp-main.773/ | [
"Meng Cao",
"Long Chen",
"Mike Zheng Shou",
"Can Zhang",
"Yuexian Zou"
] | Video grounding aims to localize the temporal segment corresponding to a sentence query from an untrimmed video. Almost all existing video grounding methods fall into two frameworks: 1) Top-down model: It predefines a set of segment candidates and then conducts segment classification and regression. 2) Bottom-up model:... | 2021.emnlp-main.773 | 10.18653/v1/2021.emnlp-main.773 | null | 2109.06085 | title_snapshot |
2021.emnlp-main.774 | COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images | https://aclanthology.org/2021.emnlp-main.774/ | [
"Ben Bogin",
"Shivanshu Gupta",
"Matt Gardner",
"Jonathan Berant"
] | While interest in models that generalize at test time to new compositions has risen in recent years, benchmarks in the visually-grounded domain have thus far been restricted to synthetic images. In this work, we propose COVR, a new test-bed for visually-grounded compositional generalization with real images. To create ... | 2021.emnlp-main.774 | 10.18653/v1/2021.emnlp-main.774 | null | 2109.10613 | title_snapshot |
2021.emnlp-main.775 | Vision-and-Language or Vision-for-Language? On Cross-Modal Influence in Multimodal Transformers | https://aclanthology.org/2021.emnlp-main.775/ | [
"Stella Frank",
"Emanuele Bugliarello",
"Desmond Elliott"
] | Pretrained vision-and-language BERTs aim to learn representations that combine information from both modalities. We propose a diagnostic method based on cross-modal input ablation to assess the extent to which these models actually integrate cross-modal information. This method involves ablating inputs from one modalit... | 2021.emnlp-main.775 | 10.18653/v1/2021.emnlp-main.775 | null | 2109.04448 | title_snapshot |
2021.emnlp-main.776 | HypMix: Hyperbolic Interpolative Data Augmentation | https://aclanthology.org/2021.emnlp-main.776/ | [
"Ramit Sawhney",
"Megh Thakkar",
"Shivam Agarwal",
"Di Jin",
"Diyi Yang",
"Lucie Flek"
] | Interpolation-based regularisation methods for data augmentation have proven to be effective for various tasks and modalities. These methods involve performing mathematical operations over the raw input samples or their latent states representations - vectors that often possess complex hierarchical geometries. However,... | 2021.emnlp-main.776 | 10.18653/v1/2021.emnlp-main.776 | null | null | null |
2021.emnlp-main.777 | Integrating Deep Event-Level and Script-Level Information for Script Event Prediction | https://aclanthology.org/2021.emnlp-main.777/ | [
"Long Bai",
"Saiping Guan",
"Jiafeng Guo",
"Zixuan Li",
"Xiaolong Jin",
"Xueqi Cheng"
] | Scripts are structured sequences of events together with the participants, which are extracted from the texts. Script event prediction aims to predict the subsequent event given the historical events in the script. Two kinds of information facilitate this task, namely, the event-level information and the script-level i... | 2021.emnlp-main.777 | 10.18653/v1/2021.emnlp-main.777 | null | 2110.15706 | title_snapshot |
2021.emnlp-main.778 | QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions | https://aclanthology.org/2021.emnlp-main.778/ | [
"Daniela Brook Weiss",
"Paul Roit",
"Ayal Klein",
"Ori Ernst",
"Ido Dagan"
] | Multi-text applications, such as multi-document summarization, are typically required to model redundancies across related texts. Current methods confronting consolidation struggle to fuse overlapping information. In order to explicitly represent content overlap, we propose to align predicate-argument relations across ... | 2021.emnlp-main.778 | 10.18653/v1/2021.emnlp-main.778 | null | 2109.12655 | title_snapshot |
2021.emnlp-main.779 | PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models | https://aclanthology.org/2021.emnlp-main.779/ | [
"Torsten Scholak",
"Nathan Schucher",
"Dzmitry Bahdanau"
] | Large pre-trained language models for textual data have an unconstrained output space; at each decoding step, they can produce any of 10,000s of sub-word tokens. When fine-tuned to target constrained formal languages like SQL, these models often generate invalid code, rendering it unusable. We propose PICARD (code avai... | 2021.emnlp-main.779 | 10.18653/v1/2021.emnlp-main.779 | null | 2109.05093 | title_snapshot |
2021.emnlp-main.780 | Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddings | https://aclanthology.org/2021.emnlp-main.780/ | [
"Marco Di Giovanni",
"Marco Brambilla"
] | Semantic sentence embeddings are usually supervisedly built minimizing distances between pairs of embeddings of sentences labelled as semantically similar by annotators. Since big labelled datasets are rare, in particular for non-English languages, and expensive, recent studies focus on unsupervised approaches that req... | 2021.emnlp-main.780 | 10.18653/v1/2021.emnlp-main.780 | null | 2110.02030 | title_snapshot |
2021.emnlp-main.781 | Guilt by Association: Emotion Intensities in Lexical Representations | https://aclanthology.org/2021.emnlp-main.781/ | [
"Shahab Raji",
"Gerard de Melo"
] | What do linguistic models reveal about the emotions associated with words? In this study, we consider the task of estimating word-level emotion intensity scores for specific emotions, exploring unsupervised, supervised, and finally a self-supervised method of extracting emotional associations from pretrained vectors an... | 2021.emnlp-main.781 | 10.18653/v1/2021.emnlp-main.781 | null | 2104.08679 | title_snapshot |
2021.emnlp-main.782 | Using Sociolinguistic Variables to Reveal Changing Attitudes Towards Sexuality and Gender | https://aclanthology.org/2021.emnlp-main.782/ | [
"Sky CH-Wang",
"David Jurgens"
] | Individuals signal aspects of their identity and beliefs through linguistic choices. Studying these choices in aggregate allows us to examine large-scale attitude shifts within a population. Here, we develop computational methods to study word choice within a sociolinguistic lexical variable—alternate words used to exp... | 2021.emnlp-main.782 | 10.18653/v1/2021.emnlp-main.782 | null | 2109.11061 | title_snapshot |
2021.emnlp-main.783 | Identifying Morality Frames in Political Tweets using Relational Learning | https://aclanthology.org/2021.emnlp-main.783/ | [
"Shamik Roy",
"Maria Leonor Pacheco",
"Dan Goldwasser"
] | Extracting moral sentiment from text is a vital component in understanding public opinion, social movements, and policy decisions. The Moral Foundation Theory identifies five moral foundations, each associated with a positive and negative polarity. However, moral sentiment is often motivated by its targets, which can c... | 2021.emnlp-main.783 | 10.18653/v1/2021.emnlp-main.783 | null | 2109.04535 | title_snapshot |
2021.emnlp-main.784 | Measuring Sentence-Level and Aspect-Level (Un)certainty in Science Communications | https://aclanthology.org/2021.emnlp-main.784/ | [
"Jiaxin Pei",
"David Jurgens"
] | Certainty and uncertainty are fundamental to science communication. Hedges have widely been used as proxies for uncertainty. However, certainty is a complex construct, with authors expressing not only the degree but the type and aspects of uncertainty in order to give the reader a certain impression of what is known. H... | 2021.emnlp-main.784 | 10.18653/v1/2021.emnlp-main.784 | null | 2109.14776 | title_snapshot |
2021.emnlp-main.785 | Assessing the Reliability of Word Embedding Gender Bias Measures | https://aclanthology.org/2021.emnlp-main.785/ | [
"Yupei Du",
"Qixiang Fang",
"Dong Nguyen"
] | Various measures have been proposed to quantify human-like social biases in word embeddings. However, bias scores based on these measures can suffer from measurement error. One indication of measurement quality is reliability, concerning the extent to which a measure produces consistent results. In this paper, we asses... | 2021.emnlp-main.785 | 10.18653/v1/2021.emnlp-main.785 | null | 2109.04732 | title_snapshot |
2021.emnlp-main.786 | Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks | https://aclanthology.org/2021.emnlp-main.786/ | [
"Hongzhan Lin",
"Jing Ma",
"Mingfei Cheng",
"Zhiwei Yang",
"Liangliang Chen",
"Guang Chen"
] | Rumors are rampant in the era of social media. Conversation structures provide valuable clues to differentiate between real and fake claims. However, existing rumor detection methods are either limited to the strict relation of user responses or oversimplify the conversation structure. In this study, to substantially r... | 2021.emnlp-main.786 | 10.18653/v1/2021.emnlp-main.786 | null | 2110.04522 | title_snapshot |
2021.emnlp-main.787 | Learning Bill Similarity with Annotated and Augmented Corpora of Bills | https://aclanthology.org/2021.emnlp-main.787/ | [
"Jiseon Kim",
"Elden Griggs",
"In Song Kim",
"Alice Oh"
] | Bill writing is a critical element of representative democracy. However, it is often overlooked that most legislative bills are derived, or even directly copied, from other bills. Despite the significance of bill-to-bill linkages for understanding the legislative process, existing approaches fail to address semantic si... | 2021.emnlp-main.787 | 10.18653/v1/2021.emnlp-main.787 | null | 2109.06527 | title_snapshot |
2021.emnlp-main.788 | SWEAT: Scoring Polarization of Topics across Different Corpora | https://aclanthology.org/2021.emnlp-main.788/ | [
"Federico Bianchi",
"Marco Marelli",
"Paolo Nicoli",
"Matteo Palmonari"
] | Understanding differences of viewpoints across corpora is a fundamental task for computational social sciences. In this paper, we propose the Sliced Word Embedding Association Test (SWEAT), a novel statistical measure to compute the relative polarization of a topical wordset across two distributional representations. T... | 2021.emnlp-main.788 | 10.18653/v1/2021.emnlp-main.788 | null | 2109.07231 | title_snapshot |
2021.emnlp-main.789 | “So You Think You’re Funny?”: Rating the Humour Quotient in Standup Comedy | https://aclanthology.org/2021.emnlp-main.789/ | [
"Anirudh Mittal",
"Pranav Jeevan P",
"Prerak Gandhi",
"Diptesh Kanojia",
"Pushpak Bhattacharyya"
] | Computational Humour (CH) has attracted the interest of Natural Language Processing and Computational Linguistics communities. Creating datasets for automatic measurement of humour quotient is difficult due to multiple possible interpretations of the content. In this work, we create a multi-modal humour-annotated datas... | 2021.emnlp-main.789 | 10.18653/v1/2021.emnlp-main.789 | null | 2110.12765 | title_snapshot |
2021.emnlp-main.790 | “Was it “stated” or was it “claimed”?: How linguistic bias affects generative language models | https://aclanthology.org/2021.emnlp-main.790/ | [
"Roma Patel",
"Ellie Pavlick"
] | People use language in subtle and nuanced ways to convey their beliefs. For instance, saying claimed instead of said casts doubt on the truthfulness of the underlying proposition, thus representing the author’s opinion on the matter. Several works have identified such linguistic classes of words that occur frequently i... | 2021.emnlp-main.790 | 10.18653/v1/2021.emnlp-main.790 | null | null | null |
2021.emnlp-main.791 | PAUSE: Positive and Annealed Unlabeled Sentence Embedding | https://aclanthology.org/2021.emnlp-main.791/ | [
"Lele Cao",
"Emil Larsson",
"Vilhelm von Ehrenheim",
"Dhiana Deva Cavalcanti Rocha",
"Anna Martin",
"Sonja Horn"
] | Sentence embedding refers to a set of effective and versatile techniques for converting raw text into numerical vector representations that can be used in a wide range of natural language processing (NLP) applications. The majority of these techniques are either supervised or unsupervised. Compared to the unsupervised ... | 2021.emnlp-main.791 | 10.18653/v1/2021.emnlp-main.791 | null | 2109.03155 | title_snapshot |
2021.emnlp-main.792 | A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders | https://aclanthology.org/2021.emnlp-main.792/ | [
"Maarten De Raedt",
"Fréderic Godin",
"Pieter Buteneers",
"Chris Develder",
"Thomas Demeester"
] | Powerful sentence encoders trained for multiple languages are on the rise. These systems are capable of embedding a wide range of linguistic properties into vector representations. While explicit probing tasks can be used to verify the presence of specific linguistic properties, it is unclear whether the vector represe... | 2021.emnlp-main.792 | 10.18653/v1/2021.emnlp-main.792 | null | 2104.03630 | title_snapshot |
2021.emnlp-main.793 | An Information-Theoretic Characterization of Morphological Fusion | https://aclanthology.org/2021.emnlp-main.793/ | [
"Neil Rathi",
"Michael Hahn",
"Richard Futrell"
] | Linguistic typology generally divides synthetic languages into groups based on their morphological fusion. However, this measure has long been thought to be best considered a matter of degree. We present an information-theoretic measure, called informational fusion, to quantify the degree of fusion of a given set of mo... | 2021.emnlp-main.793 | 10.18653/v1/2021.emnlp-main.793 | null | null | null |
2021.emnlp-main.794 | The Effect of Efficient Messaging and Input Variability on Neural-Agent Iterated Language Learning | https://aclanthology.org/2021.emnlp-main.794/ | [
"Yuchen Lian",
"Arianna Bisazza",
"Tessa Verhoef"
] | Natural languages display a trade-off among different strategies to convey syntactic structure, such as word order or inflection. This trade-off, however, has not appeared in recent simulations of iterated language learning with neural network agents (Chaabouni et al., 2019b). We re-evaluate this result in light of thr... | 2021.emnlp-main.794 | 10.18653/v1/2021.emnlp-main.794 | null | 2104.07637 | title_snapshot |
2021.emnlp-main.795 | On Classifying whether Two Texts are on the Same Side of an Argument | https://aclanthology.org/2021.emnlp-main.795/ | [
"Erik Körner",
"Gregor Wiedemann",
"Ahmad Dawar Hakimi",
"Gerhard Heyer",
"Martin Potthast"
] | To ease the difficulty of argument stance classification, the task of same side stance classification (S3C) has been proposed. In contrast to actual stance classification, which requires a substantial amount of domain knowledge to identify whether an argument is in favor or against a certain issue, it is argued that, f... | 2021.emnlp-main.795 | 10.18653/v1/2021.emnlp-main.795 | null | null | null |
2021.emnlp-main.796 | Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study | https://aclanthology.org/2021.emnlp-main.796/ | [
"Ranran Zhen",
"Rui Wang",
"Guohong Fu",
"Chengguo Lv",
"Meishan Zhang"
] | Opinion Role Labeling (ORL), aiming to identify the key roles of opinion, has received increasing interest. Unlike most of the previous works focusing on the English language, in this paper, we present the first work of Chinese ORL. We construct a Chinese dataset by manually translating and projecting annotations from ... | 2021.emnlp-main.796 | 10.18653/v1/2021.emnlp-main.796 | null | null | null |
2021.emnlp-main.797 | MassiveSumm: a very large-scale, very multilingual, news summarisation dataset | https://aclanthology.org/2021.emnlp-main.797/ | [
"Daniel Varab",
"Natalie Schluter"
] | Current research in automatic summarisation is unapologetically anglo-centered–a persistent state-of-affairs, which also predates neural net approaches. High-quality automatic summarisation datasets are notoriously expensive to create, posing a challenge for any language. However, with digitalisation, archiving, and so... | 2021.emnlp-main.797 | 10.18653/v1/2021.emnlp-main.797 | null | null | null |
2021.emnlp-main.798 | AUTOSUMM: Automatic Model Creation for Text Summarization | https://aclanthology.org/2021.emnlp-main.798/ | [
"Sharmila Reddy Nangi",
"Atharv Tyagi",
"Jay Mundra",
"Sagnik Mukherjee",
"Raj Snehal",
"Niyati Chhaya",
"Aparna Garimella"
] | Recent efforts to develop deep learning models for text generation tasks such as extractive and abstractive summarization have resulted in state-of-the-art performances on various datasets. However, obtaining the best model configuration for a given dataset requires an extensive knowledge of deep learning specifics lik... | 2021.emnlp-main.798 | 10.18653/v1/2021.emnlp-main.798 | null | null | null |
2021.emnlp-main.799 | Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation Output | https://aclanthology.org/2021.emnlp-main.799/ | [
"Raksha Shenoy",
"Nico Herbig",
"Antonio Krüger",
"Josef van Genabith"
] | Compared to fully manual translation, post-editing (PE) machine translation (MT) output can save time and reduce errors. Automatic word-level quality estimation (QE) aims to predict the correctness of words in MT output and holds great promise to aid PE by flagging problematic output. Quality of QE is crucial, as incor... | 2021.emnlp-main.799 | 10.18653/v1/2021.emnlp-main.799 | null | null | null |
2021.emnlp-main.800 | UNKs Everywhere: Adapting Multilingual Language Models to New Scripts | https://aclanthology.org/2021.emnlp-main.800/ | [
"Jonas Pfeiffer",
"Ivan Vulić",
"Iryna Gurevych",
"Sebastian Ruder"
] | Massively multilingual language models such as multilingual BERT offer state-of-the-art cross-lingual transfer performance on a range of NLP tasks. However, due to limited capacity and large differences in pretraining data sizes, there is a profound performance gap between resource-rich and resource-poor target languag... | 2021.emnlp-main.800 | 10.18653/v1/2021.emnlp-main.800 | null | 2012.15562 | title_snapshot |
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