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20242026
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cs.CL2026

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

Yinghui He, Ling Yang, Jiarui Liu +6

Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result t…

cs.CL2026

MixSD: Mixed Contextual Self-Distillation for Knowledge Injection

Jiarui Liu, Lechen Zhang, Yongjin Yang +5

Supervised fine-tuning (SFT) is widely used to inject new knowledge into language models, but it often degrades pretrained capabilities such as reasoning and general-domain perform…

cs.CL2026

OdysSim: Building Foundation Models for Human Behavior Simulation

Xuhui Zhou, Weiwei Sun, Weihua Du +6

Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven post-training pulls them toward a homog…

cs.CL2026

Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision

Yinghui He, Simran Kaur, Adithya Bhaskar +7

Current post-training methods in verifiable settings fall into two categories. Reinforcement learning (RLVR) relies on binary rewards, which are broadly applicable and powerful, bu…

cs.CL2026

PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf

Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner +17

Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because revi…

cs.CL2026

Re-Centering Humans in LLM Personalization

Lechen Zhang, Jiarui Liu, Tal August

Despite growing interest, most evaluations of large language models' (LLMs') personalization abilities have relied on synthetic data. It remains unclear how well current personaliz…