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cs.IR2026
Beyond Self-Knowledge: Propagating Uncertainty Across Reasoning and Retrieval in LLMs
Chandan Kumar Sah, Li Zhang, Xiaoli Lian
Retrieval-augmented generation improves knowledge-intensive question answering, but indiscriminate retrieval can introduce irrelevant evidence and unnecessary computation. We inves…
cs.SE2026
Beyond "What to Retrieve": Uncertainty in Retrieval-Augmented Code Generation
Chandan Kumar Sah, Li Zhang, Xiaoli Lian
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…