Abstract
Human-like chatbots necessitate the use of commonsense reasoning in order to effectively comprehend and respond to implicit information present within conversations. Achieving such coherence and informativeness in responses, however, is a non-trivial task. Even for large language models (LLMs), the task of identifying and aggregating key evidence within a single hop presents a substantial challenge. This complexity arises because such evidence is scattered across multiple turns in a conversation, thus necessitating integration over multiple hops. Hence, our focus is to facilitate such multi-hop reasoning over a dialogue context, namely dialogue chain-of-thought (CoT) reasoning. To this end, we propose a knowledge distillation framework that leverages LLMs as unreliable teachers and selectively distills consistent and helpful rationales via alignment filters. We further present DOCTOR, a DialOgue Chain-of-ThOught Reasoner that provides reliable CoT rationales for response generation. We conduct extensive experiments to show that enhancing dialogue agents with high-quality rationales from DOCTOR significantly improves the quality of their responses.
Original language | English (US) |
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Title of host publication | EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings |
Editors | Houda Bouamor, Juan Pino, Kalika Bali |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 5606-5632 |
Number of pages | 27 |
ISBN (Electronic) | 9798891760608 |
State | Published - 2023 |
Event | 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023 - Hybrid, Singapore, Singapore Duration: Dec 6 2023 → Dec 10 2023 |
Publication series
Name | EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings |
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Conference
Conference | 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023 |
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Country/Territory | Singapore |
City | Hybrid, Singapore |
Period | 12/6/23 → 12/10/23 |
Bibliographical note
Publisher Copyright:© 2023 Association for Computational Linguistics.