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cs.AI2026
BiasTrace: Linking Reasoning Behaviours to Biased Outputs in LLMs
Varsha Ramineni, Hossein A. Rahmani, Jerome Ramos +2
LLMs exhibit social biases that can produce inaccurate and discriminatory inferences, posing risks in high-stakes applications. While prior work has made progress in measuring and…
cs.AI2026
Interplay: Training Independent Simulators for Reference-Free Conversational Recommendation
Jerome Ramos, Feng Xia, Xi Wang +4
Training conversational recommender systems (CRS) requires extensive dialogue data, which is challenging to collect at scale. To address this, researchers have used simulated user-…
cs.AI2026
Beyond Output Critique: Self-Correction via Task Distillation
Hossein A. Rahmani, Mengting Wan, Pei Zhou +4
Large language models (LLMs) have shown promising self-correction abilities, where iterative refinement improves the quality of generated responses. However, most existing approach…