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20212026
most citedEnhancing Event-Level Sentiment Analysis with Structured Arguments

5 citations · 16 across the 21 of their papers we have counts for

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23 papers · 1 filter

cs.CL2026

Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents

Yuxuan Cai, Wei Li, Jie Zhou +4

Online lifelong learning agents must decide not only how to act but also when to consult prior experience to continually improve on long-horizon tasks. Existing methods typically r…

cs.CL2025

DiaCBT: A Long-Periodic Dialogue Corpus Guided by Cognitive Conceptualization Diagram for CBT-based Psychological Counseling

Yougen Zhou, Ningning Zhou, Qin Chen +3

Psychotherapy reaches only a small fraction of individuals suffering from mental disorders due to social stigma and the limited availability of therapists. Large language models (L…

cs.CL2025

Teaching LLMs for Step-Level Automatic Math Correction via Reinforcement Learning

Junsong Li, Jie Zhou, Yutao Yang +7

Automatic math correction aims to check students' solutions to mathematical problems via artificial intelligence technologies. Most existing studies focus on judging the final answ…

cs.CL2025

Code-Driven Inductive Synthesis: Enhancing Reasoning Abilities of Large Language Models with Sequences

Kedi Chen, Zhikai Lei, Fan Zhang +7

Large language models make remarkable progress in reasoning capabilities. Existing works focus mainly on deductive reasoning tasks (e.g., code and math), while another type of reas…

cs.CL20252 cited

LLM-KT: Aligning Large Language Models with Knowledge Tracing using a Plug-and-Play Instruction

Ziwei Wang, Jie Zhou, Qin Chen +5

The knowledge tracing (KT) problem is an extremely important topic in personalized education, which aims to predict whether students can correctly answer the next question based on…

cs.CL2025

Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection

Kedi Chen, Qin Chen, Jie Zhou +7

Large Language Models (LLMs) are prone to hallucination with non-factual or unfaithful statements, which undermines the applications in real-world scenarios. Recent researches focu…