March 22, 2024, 4:42 a.m. | Sehee Lim, Yejin Kim, Chi-Hyun Choi, Jy-yong Sohn, Byung-Hoon Kim

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.14255v1 Announce Type: cross
Abstract: Improving the accessibility of psychotherapy with the aid of Large Language Models (LLMs) is garnering a significant attention in recent years. Recognizing cognitive distortions from the interviewee's utterances can be an essential part of psychotherapy, especially for cognitive behavioral therapy. In this paper, we propose ERD, which improves LLM-based cognitive distortion classification performance with the aid of additional modules of (1) extracting the parts related to cognitive distortion, and (2) debating the reasoning steps by …

abstract accessibility arxiv attention classification cognitive cs.cl cs.lg framework improving language language models large language large language models llm llm reasoning llms paper part reasoning therapy type

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