Large language models (LLMs) are increasingly discussed as tools for peer review, but their value is often assessed through human-likeness, perceived usefulness, or textual overlap with reviewer comments. This study shifts attention from whether LLMs resemble human reviewers to what functions of scientific critique the...
YunHong Yang, Mike Thelwall, Guo-Xiu He· 0 citations
Experiments show that EASD consistently improves accuracy over standard SD and reward-guided variants while maintaining comparable inference efficiency, suggesting that speculative decoding can serve not only as an acceleration method but also as an effective mechanism for improving reasoning quality.
Tiancheng Su, Meicong Zhang, Guoxiu He· 3 citations
Experiments show that StructPO improves semantic alignment, structural rationality and inference efficiency over workflow-based baselines, generalizes to out-of-domain settings, and remains competitive with GPT-5.1 in human evaluation when scaled to Qwen3-32B.
Meicong Zhang, Tiancheng Su, Jia-Hao Cheng et al.· 0 citations
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