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#Reinforcement Learning with Verifiable Rewards

Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text

Intermediate

Ximing Lu, David Acuna et al.Jan 30arXiv

Golden Goose turns messy internet text into clean multiple-choice puzzles that computers can learn from and get automatic rewards for.

#Reinforcement Learning with Verifiable Rewards#Golden Goose#GooseReason-0.7M

Exploring Reasoning Reward Model for Agents

Intermediate

Kaixuan Fan, Kaituo Feng et al.Jan 29arXiv

The paper teaches AI agents better by grading not just their final answers, but also how they think and use tools along the way.

#Agentic Reinforcement Learning#Reasoning Reward Model#Process Supervision

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification

Beginner

Yiju Guo, Tianyi Hu et al.Jan 29arXiv

This paper shows that many reasoning failures in AI are caused by just a few distracting words in the prompt, not because the problems are too hard.

#LENS#Interference Tokens#Reinforcement Learning with Verifiable Rewards

LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR

Intermediate

Said Taghadouini, Adrien Cavaillès et al.Jan 20arXiv

LightOnOCR-2-1B is a single, compact AI model that reads PDF pages and scans and turns them into clean, well-ordered text without using fragile multi-step OCR pipelines.

#LightOnOCR-2-1B#end-to-end OCR#vision-language model