Attention as Selector: Unlocking VLM Attention for Long Document Page Retrieval (2026)
Long documents rarely fit into a vision-language model's context, so DocQA pipelines usually pick a few pages first.
How to Improve LLMs' Performance on Specific Languages: A Perspective on LLM-Derived Language Similarity (2026)
LLMs perform unevenly across languages. When target-language training data is scarce, practitioners usually pick a related "donor" language for fine-tuning based on linguistic typology. This work questions whether typology matches how models themselves perceive language similarity. The authors propose three…
N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization (2026)
RL fine-tuning methods such as GRPO depend on the rollout phase producing varied reasoning paths. Existing approaches have drawbacks. Ordinary token sampling tends to produce near-duplicate solutions that differ only in wording or operand order. Adding Gaussian noise to embeddings, by contrast, often moves tokens to…
Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward (2026)
Reinforcement learning with verifiable rewards (RLVR) works well for LLM post-training, but it needs gold answers or task-specific checkers, which limits its use in new domains.

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Updated 2 November 2026