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From the 1 of 23 linked papers with an AI index.

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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

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.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

Contextual Drag: How Errors in the Context Affect LLM Reasoning

Yun Cheng, Xingyu Zhu, Haoyu Zhao +1

Central to many self-improvement pipelines for large language models (LLMs) is the assumption that models can improve by reflecting on past mistakes. We study a phenomenon termed c…

cs.CL2025

Can Models Learn Skill Composition from Examples?

Haoyu Zhao, Simran Kaur, Dingli Yu +2

As large language models (LLMs) become increasingly advanced, their ability to exhibit compositional generalization -- the capacity to combine learned skills in novel ways not enco…