12 papers
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,…
SURE: Synergistic Uncertainty-aware Reasoning for Multimodal Emotion Recognition in Conversations
Yiqiang Cai, Chengyan Wu, Bolei Ma +4
Multimodal emotion recognition in conversations (MERC) requires integrating multimodal signals while being robust to noise and modeling contextual reasoning. Existing approaches of…
Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation
Ziwei Gong, Yanda Chen, Julia Hirschberg +4
Large language models (LLMs) encode knowledge with varying degrees of confidence. When responding to queries, models face an inherent trade-off: they can generate responses that ar…
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,…
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…
Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects
Chengyan Wu, Yiqiang Cai, Yang Liu +5
While text-based emotion recognition methods have achieved notable success, real-world dialogue systems often demand a more nuanced emotional understanding than any single modality…