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Honghao Liu

ACL 2026×2推理对齐与偏好强化学习与后训练安全可解释性
新星分新星
60
一作贡献30
核心/参与5
方向广度10
合作网络6
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #6/8ACL 2026Findings· Findings of ACL

S elect2 R eason: Efficient Instruction-Tuning Data Selection for Long- C o T Reasoning

Cehao Yang · Xueyuan Lin · Xiaojun Wu · Chengjin Xu · Xuhui Jiang · Honghao Liu · Hui Xiong · Jian Guo

摘要

A practical approach to activate long chain-of-thoughts reasoning ability in large language models is to perform supervised fine-tuning on instruction datasets synthesized by strong large reasoning models, offering a cost-effective alternative to reinforcement learning. However, large-scale instr...

推理对齐与偏好强化学习与后训练OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

Conflicts Make Large Reasoning Models Vulnerable to Attacks

Honghao Liu · Chengjin Xu · Xuhui Jiang · Cehao Yang · Shengming Yin · Zhengwu Ma · Lionel Ni · Jian Guo

摘要

Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives remains insufficiently understood. This work investigates how LRMs respond to harmful queries when confronted with two categories of conflicts: interna...

安全可解释性评测与基准OpenReview 项目页

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