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cs.CL2026
Beyond Calibration: Temporal LLM Confidence Assessment Across Languages and Local Settings
Sahil Kale
Large language models are expected to estimate their own uncertainty, with confidence signals used to guide retrieval, adaptive compute allocation, routing, and selective abstentio…
cs.CL2026
ConceptGuard: Benchmarking Context-Sensitive Unlearning in Large Language Models
Sahil Kale, Ian Harris
Large Language Models (LLMs) often require selective removal of harmful or sensitive knowledge, called unlearning, yet existing benchmarks evaluate this capability incompletely. Th…
cs.CL2026
Future Confidence Distillation in Large Language Models
Sahil Kale
Reliable confidence estimation is essential for deploying large language models (LLMs) in confidence-aware systems, where downstream decisions such as retrieval, tool use, and adap…