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cs.CL2026
Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference
Xuwen Zhou, Fangxin Liu, Chao Wang +5
Speculative decoding accelerates autoregressive generation by letting draft tokens bypass full verification, but conventional frameworks suffer from frequent false rejections, part…
cs.CL2025
From Faithfulness to Correctness: Generative Reward Models that Think Critically
Qiyao Ma, Yunsheng Shi, Hongtao Tian +3
Through reinforcement learning with verifiable rewards (RLVR), large language models have achieved substantial progress in domains with easily verifiable outcomes, such as mathemat…