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cs.CL2026

Self-Authored Verification Is Unreliable in Heuristic Self-Improving Agents

Diandian Guo, Cong Cao, Fangfang Yuan +3

Self-improving agents accumulate capability by repeatedly rewriting procedural policies, controllers, or heuristic rules. They typically rely on self-authored tests or metrics to d…

cs.CL2026

MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues

Diandian Guo, Fangfang Yuan, Cong Cao +5

The prevalence of sarcasm in multimodal dialogues on the social platforms presents a crucial yet challenging task for understanding the true intent behind online content. Comprehen…

cs.CL2026

Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning

Yu Liu, Wenxiao Zhang, Diandian Guo +6

Retrieval-augmented generation (RAG) can achieve strong answer accuracy on multi-hop questions, but outcome-level rewards often leave reasoning traces weakly grounded and difficult…

cs.CL2025

Emotion Transfer with Enhanced Prototype for Unseen Emotion Recognition in Conversation

Kun Peng, Cong Cao, Hao Peng +5

Current Emotion Recognition in Conversation (ERC) research follows a closed-domain assumption. However, there is no clear consensus on emotion classification in psychology, which p…

cs.CL2025

Dialogues Aspect-based Sentiment Quadruple Extraction via Structural Entropy Minimization Partitioning

Kun Peng, Cong Cao, Hao Peng +5

Dialogues Aspect-based Sentiment Quadruple Extraction (DiaASQ) aims to extract all target-aspect-opinion-sentiment quadruples from a given multi-round, multi-participant dialogue.…

cs.CL2025

T-T: Table Transformer for Tagging-based Aspect Sentiment Triplet Extraction

Kun Peng, Chaodong Tong, Cong Cao +6

Aspect sentiment triplet extraction (ASTE) aims to extract triplets composed of aspect terms, opinion terms, and sentiment polarities from given sentences. The table tagging method…