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cs.CL2026
BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences
Ru Peng, Haokai Xu, Xijun Gu +11
While data synthesis for large language models (LLMs) is prevalent, it primarily targets domains with verifiable answers, overlooking open-ended humanities and social sciences (HSS…
cs.CL2026
Reasoning Error from Known Fact: Step-Level Self-Consistency Group Relative Policy Optimization for LLMs
Xiaomeng Hu, Jiaqi Hu, Hao Chen +4
With the rapid advancement of large language models (LLMs), modern systems not only possess strong foundational capabilities and extensive knowledge, but can also solve complex pro…
cs.AI2026
Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
Zhanming Shen, Jintao Tong, Shaotian Yan +9
On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference solutions provides token-lev…