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cs.CL2026
Uncertainty-Aware Budget Allocation for Adaptive Test-Time Reasoning
Manh Nguyen, Sunil Gupta, Hung Le
Sampling multiple responses improves language model reasoning, but uniform compute allocation is inefficient: easy questions are over-sampled while hard questions remain under-expl…
cs.CL2026
Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score
Manh Nguyen, Sunil Gupta, Hung Le
Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challenging, especially when correctne…
cs.CL2025
GRAD: Graph-Retrieved Adaptive Decoding for Hallucination Mitigation
Manh Nguyen, Sunil Gupta, Dai Do +1
Hallucination mitigation remains a persistent challenge for large language models (LLMs), even as model scales grow. Existing approaches often rely on external knowledge sources, s…