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RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs.

, , , , , and . ACL (1), page 7716-7733. Association for Computational Linguistics, (2023)

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Through the Glance Mug: A Familiar Artefact to Support Opportunistic Search in Meetings., , , , , , , and . TEI, page 674-683. ACM, (2018)Lexicon Learning for Few Shot Sequence Modeling., and . ACL/IJCNLP (1), page 4934-4946. Association for Computational Linguistics, (2021)Pre-Trained Language Models for Interactive Decision-Making., , , , , , , , , and 4 other author(s). NeurIPS, (2022)Towards Tracing Knowledge in Language Models Back to the Training Data., , , , , , and . EMNLP (Findings), page 2429-2446. Association for Computational Linguistics, (2022)Compositional Semantic Parsing with Large Language Models., , , , , , , and . ICLR, OpenReview.net, (2023)Subspace Regularizers for Few-Shot Class Incremental Learning., , , and . ICLR, OpenReview.net, (2022)In-Context Language Learning: Architectures and Algorithms., , , and . ICML, OpenReview.net, (2024)Compositional Semantic Parsing with Large Language Models., , , , , , , and . CoRR, (2022)Learning to Recombine and Resample Data For Compositional Generalization., , and . ICLR, OpenReview.net, (2021)Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks., , , , , , , , and . NAACL-HLT, page 1819-1862. Association for Computational Linguistics, (2024)