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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.IR2026

Beyond Self-Knowledge: Propagating Uncertainty Across Reasoning and Retrieval in LLMs

Chandan Kumar Sah, Xiaoli Lian, Li Zhang

The paper introduces BeyondUncertainty, a method that uses confidence estimates from black‑box language models to decide whether to retrieve external evidence for question answerin…

cs.SE2026

Beyond "What to Retrieve": Uncertainty in Retrieval-Augmented Code Generation

Chandan Kumar Sah, Xiaoli Lian, Li Zhang

Repository-level code generation relies on heterogeneous evidence whose relevance, compatibility, and completeness are inherently uncertain. Similar-code examples, repository conte…

cs.AI2026

Uncertainty and Fairness Awareness in LLM-Based Recommendation Systems

Chandan Kumar Sah, Xiaoli Lian, Li Zhang +2

Large language models (LLMs) enable powerful zero-shot recommendations by leveraging broad contextual knowledge, yet predictive uncertainty and embedded biases threaten reliability…

cs.IR2025

FairEval: Evaluating Fairness in LLM-Based Recommendations with Personality Awareness

Chandan Kumar Sah, Xiaoli Lian, Tony Xu +1

Recent advances in Large Language Models (LLMs) have enabled their application to recommender systems (RecLLMs), yet concerns remain regarding fairness across demographic and psych…

cs.CV2025

Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection

Chandan Kumar Sah, Ankit Kumar Shaw, Xiaoli Lian +5

Autonomous vehicles (AVs) require reliable traffic sign recognition and robust lane detection capabilities to ensure safe navigation in complex and dynamic environments. This paper…