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20232025
most citedAutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling

5 citations · 13 across the 10 of their papers we have counts for

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Showing cs.CLShow all

12 papers · 1 filter

cs.CL20252 cited

A Survey on Large Language Model Benchmarks

Shiwen Ni, Guhong Chen, Shuaimin Li +11

In recent years, with the rapid development of the depth and breadth of large language models' capabilities, various corresponding evaluation benchmarks have been emerging in incre…

cs.CL2025

xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking

Sunbowen Lee, Shiwen Ni, Chi Wei +7

Safety alignment mechanism are essential for preventing large language models (LLMs) from generating harmful information or unethical content. However, cleverly crafted prompts can…

cs.CL20255 cited

AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling

Ancheng Xu, Di Yang, Renhao Li +13

Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues, while online automated counseling offers a potential…

cs.CL2024

DualCoTs: Dual Chain-of-Thoughts Prompting for Sentiment Lexicon Expansion of Idioms

Fuqiang Niu, Minghuan Tan, Bowen Zhang +2

Idioms represent a ubiquitous vehicle for conveying sentiments in the realm of everyday discourse, rendering the nuanced analysis of idiom sentiment crucial for a comprehensive und…

cs.CL2024

Training on the Benchmark Is Not All You Need

Shiwen Ni, Xiangtao Kong, Chengming Li +4

The success of Large Language Models (LLMs) relies heavily on the huge amount of pre-training data learned in the pre-training phase. The opacity of the pre-training process and th…

cs.CL20241 cited

Improving In-Context Learning with Prediction Feedback for Sentiment Analysis

Hongling Xu, Qianlong Wang, Yice Zhang +4

Large language models (LLMs) have achieved promising results in sentiment analysis through the in-context learning (ICL) paradigm. However, their ability to distinguish subtle sent…