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#policy gradient

Reinforced Attention Learning

Intermediate

Bangzheng Li, Jianmo Ni et al.Feb 4arXiv

This paper teaches AI to pay attention better by training its focus, not just its words.

#Reinforced Attention Learning#attention policy#multimodal LLM

Not triaged yet

BatCoder: Self-Supervised Bidirectional Code-Documentation Learning via Back-Translation

Intermediate

Jingwen Xu, Yiyang Lu et al.Jan 30arXiv

BatCoder teaches a code model to write both code and its documentation by doing a round trip: from code to docs and back to code.

#back-translation#self-supervised learning#reinforcement learning for code

Not triaged yet

Learning to Discover at Test Time

Intermediate

Mert Yuksekgonul, Daniel Koceja et al.Jan 22arXiv

This paper shows how to keep training a language model while it is solving one hard, real problem, so it can discover a single, truly great answer instead of many average ones.

#test-time training#reinforcement learning#entropic objective

Not triaged yet

JudgeRLVR: Judge First, Generate Second for Efficient Reasoning

Intermediate

Jiangshan Duo, Hanyu Li et al.Jan 13arXiv

JudgeRLVR teaches a model to be a strict judge of answers before it learns to generate them, which trims bad ideas early.

#RLVR#judge-then-generate#discriminative supervision

Not triaged yet

Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning

Intermediate

Ming Chen, Sheng Tang et al.Dec 6arXiv

The paper shows that making a model write a number as a sequence of digits and then grading the whole number at the end works better than grading each digit separately.

#decoding-based regression#sequence-level reward#reinforcement learning

Not triaged yet