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Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs.

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Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision., , , и . CoRR, (2020)Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision., , , и . AAAI, стр. 12592-12601. AAAI Press, (2021)Is Everything in Order? A Simple Way to Order Sentences., , и . EMNLP (1), стр. 10769-10779. Association for Computational Linguistics, (2021)Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs., , , , , , и . CoRR, (2023)“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding, , , , , и . Findings of the Association for Computational Linguistics: EMNLP 2021, Association for Computational Linguistics, (2021)STEER: Unified Style Transfer with Expert Reinforcement., , , , , и . EMNLP (Findings), стр. 7546-7562. Association for Computational Linguistics, (2023)MacGyver: Are Large Language Models Creative Problem Solvers?, , , , , , , , и . CoRR, (2023)Towards Inter-character Relationship-driven Story Generation., , und . EMNLP, Seite 8970-8987. Association for Computational Linguistics, (2022)WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild., , , , , , , , und . CoRR, (2024)Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning., , , , , , , , , und 7 andere Autor(en). EMNLP, Seite 6863-6883. Association for Computational Linguistics, (2023)