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cs.CL2026
Adaptive Decoding via Test-Time Policy Learning for Self-Improving Generation
Asmita Bhardwaj, Yuya Jeremy Ong, Eelaaf Zahid +1
Decoding strategies largely determine the quality of Large Language Model (LLM) outputs, yet widely used heuristics such as greedy or fixed temperature/top-p decoding are static an…
cs.CL2026
Evaluating Ill-Defined Tasks in Large Language Models
Yi Zhou, Basel Shbita
Many evaluations of Large Language Models (LLMs) target tasks that are inherently ill-defined, with unclear input and output spaces and ambiguous success criteria. We analyze why e…