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From the 1 of 12 linked papers with an AI index.

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12 papers

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

T^2MLR: Transformer with Temporal Middle-Layer Recurrence

Ziyang Cai, Xingyu Zhu, Yihe Dong +2

The paper proposes T²MLR, a transformer variant that injects a cached middle‑layer representation from the previous token into an earlier layer of the current token, allowing inter…

cs.AI2026

Rethinking On-Policy Self-Distillation for Thinking Models

Simran Kaur, Narutatsu Ri, Yinghui He +2

Self-distillation is a promising recipe for self-improvement in language models. In this setting, a model can serve as its own teacher when given privileged information, such as a…

cs.AI2026

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR

Yongjin Yang, Jiarui Liu, Yinghui He +3

Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematics, programming, and science.…

cs.LG2026

DCD-PFN: A Decoupling-Aware Foundation Model for Causal Discovery

Zhengkang Guan, Yikang Chen, Yi He +5

Causal discovery is critical for understanding complex data-generating mechanisms, yet traditional algorithms often struggle with highly non-linear and noisy systems, or suffer fro…

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…