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20242026
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cs.CL2026

An Interactive Paradigm for Deep Research

Lin Ai, Victor S. Bursztyn, Xiang Chen +2

Recent advances in large language models (LLMs) have enabled deep research systems that synthesize comprehensive, report-style answers to open-ended queries by combining retrieval,…

cs.CL20261 cited

A Review of Incorporating Psychological Theories in LLMs

Zizhou Liu, Ziwei Gong, Lin Ai +5

Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop,…

cs.CL2026

Detecting Mental Manipulation in Speech via Synthetic Multi-Speaker Dialogue

Run Chen, Wen Liang, Ziwei Gong +2

Mental manipulation, the strategic use of language to covertly influence or exploit others, is a newly emerging task in computational social reasoning. Prior work has focused exclu…

cs.CL2025

Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues

David Sasu, Zehui Wu, Ziwei Gong +5

In this paper, we introduce the Akan Conversation Emotion (ACE) dataset, the first multimodal emotion dialogue dataset for an African language, addressing the significant lack of r…

cs.CL2025

ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data?

Zheng Hui, Zhaoxiao Guo, Hang Zhao +5

Effective toxic content detection relies heavily on high-quality and diverse data, which serve as the foundation for robust content moderation models. Synthetic data has become a c…

cs.CL2025

PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent

Jiateng Liu, Lin Ai, Zizhou Liu +6

Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the…