Author

Xing Sun

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#artificial intelligence May 2026

Revisiting Reinforcement Learning with Verifiable Rewards from a Contrastive Perspective

ConSPO is a Contrastive Sequence-level Policy Optimization method that uses length-normalized sequence log-probabilities as rollout scores and contrasts verified positive rollouts against negative distractors within the same group, and outperforms strong baselines on challenging reasoning benchmarks.

Feng Zhang, Xin-Hong Ma, Zi-Qiang Dong et al. · arXiv.org · 1 citation

#artificial intelligence Mar 2026

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

This work proposes HISA (Hierarchical Indexed Sparse Attention), a plug-and-play replacement for the indexer that rewrites the search path from a flat token scan into a two-stage hierarchical procedure: a block-level coarse filtering stage that scores pooled block representations to discard irrelevant regions, followed...

Yufei Xu, Fan-Xu Meng, Fan Jiang et al. · arXiv.org · 10 citations · ⚡1