26 citations · 36 across the 9 of their papers we have counts for
6 papers · 1 filter
Adversarially Robust Geometric Safety Certificates for Nonholonomic Robots Against Maneuvering Obstacles
Chandan Kumar Sah, Bazeela Banday, Jishnu Keshavan
Safe navigation against obstacles that can actively maneuver within bounded capabilities remains challenging: robust control barrier function methods typically treat obstacle actio…
Exact Feasibility Certification and Optimal Responsibility Allocation for Multi-Robot CBF Safety Filters
Chandan Kumar Sah, Jishnu Keshavan
Multi-robot Control Barrier Function (CBF) safety filters can become infeasible, but a failed quadratic program (QP) does not indicate why the conflict occurred or how to resolve i…
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…
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…
SACK : Safe Active Continual Koopman Learning for Uncertain Systems with Contractive Guarantees
Chandan Kumar Sah, Rajpal Singh, Jishnu Keshavan
Koopman operator theory provides a powerful framework for representing nonlinear dynamics through a linear operator acting on lifted observables, enabling the use of linear control…
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…