Evgeny Kotelnikov
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The paper demonstrates that using Reinforcement Learning from Verifiable Rewards (RLVR) significantly improves small language models' functional correctness in code generation, particularly when combining unit-test and static-analysis feedback.
This paper investigates if team-based interaction improves LLM performance on complex reasoning tasks (ChGK), finding that structured team strategies significantly boost accuracy by acting as error-filtering mechanisms.
Papers
Improving Small Language Models for Code Generation with Reinforcement Learning from Verification Feedback
The paper demonstrates that using Reinforcement Learning from Verifiable Rewards (RLVR) significantly improves small language models' functional correctness in code generation, particularly when combi…