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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 45 1 Blindness to Modality Helps Entailment Graph Mining ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Mark; Bijl de Vroe, Sander. - : Underline Science Inc., 2021 BASE Show details 2 WebSRC: A Dataset for Web-Based Structural Reading Comprehension ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Xingyu. - : Underline Science Inc., 2021 BASE Show details 3 Semantic Categorization of Social Knowledge for Commonsense Question Answering ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Wang, Gengyu. - : Underline Science Inc., 2021 BASE Show details 4 ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Baylon, Julia; Han, Rujun. - : Underline Science Inc., 2021 BASE Show details 5 CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Piyush; Akula, Arjun. - : Underline Science Inc., 2021 BASE Show details 6 Foreseeing the Benefits of Incidental Supervision ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dan; He, Hangfeng. - : Underline Science Inc., 2021 BASE Show details 7 PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Lewis, Patrick. - : Underline Science Inc., 2021 BASE Show details 8 Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ju, Yiming; Zhang, Yuanzhe. - : Underline Science Inc., 2021 BASE Show details 9 Mapping probability word problems to executable representations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Daelemans, Walter; Davis, Jesse. - : Underline Science Inc., 2021 BASE Show details 10 Contrastive Domain Adaptation for Question Answering using Limited Text Corpora ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Feuerriegel, Stefan; Kratzwald, Bernhard. - : Underline Science Inc., 2021 BASE Show details 11 Smoothing Dialogue States for Open Conversational Machine Reading ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ouyang, Siru; Zhang, Zhuosheng. - : Underline Science Inc., 2021 BASE Show details 12 How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jiang, Zhengbao. - : Underline Science Inc., 2021 BASE Show details 13 Evaluation Paradigms in Question Answering ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Jordan; Rodriguez, Pedro. - : Underline Science Inc., 2021 BASE Show details 14 FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Srinivasan; Ghoshal, Asish. - : Underline Science Inc., 2021 BASE Show details 15 Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bartolo, Max; Jia, Robin; Kiela, Douwe; Riedel, Sebastian; Stenetorp, Pontus; Thrush, Tristan. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.696/ Abstract: Despite recent progress, state-of-the-art question answering models remain vulnerable to a variety of adversarial attacks. While dynamic adversarial data collection, in which a human annotator tries to write examples that fool a model-in-the-loop, can improve model robustness, this process is expensive which limits the scale of the collected data. In this work, we are the first to use synthetic adversarial data generation to make question answering models more robust to human adversaries. We develop a data generation pipeline that selects source passages, identifies candidate answers, generates questions, then finally filters or re-labels them to improve quality. Using this approach, we amplify a smaller human-written adversarial dataset to a much larger set of synthetic question-answer pairs. By incorporating our synthetic data, we improve the state-of-the-art on the AdversarialQA dataset by 3.7F1 and improve model generalisation ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Question-Answering Systems URL: https://dx.doi.org/10.48448/f04n-c312 https://underline.io/lecture/37811-improving-question-answering-model-robustness-with-synthetic-adversarial-data-generation BASE Hide details 16 Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Belfer, Robert; Kulshreshtha, Devang. - : Underline Science Inc., 2021 BASE Show details 17 Zero-Shot Dialogue State Tracking via Cross-Task Transfer ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cho, Eunjoon; Crook, Paul. - : Underline Science Inc., 2021 BASE Show details 18 Case-based Reasoning for Natural Language Queries over Knowledge Bases ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Das, Rajarshi; Godbole, Ameya. - : Underline Science Inc., 2021 BASE Show details 19 Will this Question be Answered? Question Filtering via Answer Model Distillation for Efficient Question Answering ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Garg, Siddhant; Moschitti, Alessandro. - : Underline Science Inc., 2021 BASE Show details 20 Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Rebuffel, Clément. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3

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