
Title |
|---|
![]() Understand the Implication: Learning to Think for Pragmatic UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL), 2025 |
![]() Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL), 2025 |
![]() Interpreting Answers to Yes-No Questions in User-Generated ContentConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
![]() Pre-Training to Learn in ContextAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 |
![]() Learning to Initialize: Can Meta Learning Improve Cross-task
Generalization in Prompt Tuning?Annual Meeting of the Association for Computational Linguistics (ACL), 2023 |
![]() Resolving Indirect Referring Expressions for Entity SelectionAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
![]() (QA): Question Answering with Questionable AssumptionsAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
![]() N-best Response-based Analysis of Contradiction-awareness in Neural
Response Generation ModelsSIGDIAL Conferences (SIGDIAL), 2022 |
![]() Few-shot Adaptation Works with UnpredicTable DataAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 |
![]() KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in
Low-Resource NLPInternational Conference on Learning Representations (ICLR), 2022 |
![]() Eliciting and Understanding Cross-Task Skills with Task-Level
Mixture-of-ExpertsConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 |
![]() MetaICL: Learning to Learn In ContextNorth American Chapter of the Association for Computational Linguistics (NAACL), 2021 |
![]() CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in
NLPConference on Empirical Methods in Natural Language Processing (EMNLP), 2021 |
![]() Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation
for Few-shot LearningConference on Empirical Methods in Natural Language Processing (EMNLP), 2021 |