---
title: "Chao Xue — papers of 2026 — 4 papers, the most cited first"
description: "Chao Xue — papers of 2026: 4 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Chao Xue — papers of 2026 — 4 papers, the most cited first

4 papers · [all years of Chao Xue](https://md.research.elamur.ai/free/en/authors/chao-xue/#years)

**[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*

**[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*

**[Beyond Token Length: Step Pruner for Efficient and Accurate Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-token-length-step-pruner/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Canhui Wu, Qiong Cao, Chang Li, et al.*2026 · 2 citations*

**[Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling](https://md.research.elamur.ai/free/en/papers/wang-2026-universally-empowering-zeroth-order-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Wang, Li Shen, Liang Ding, et al.*2026*