LC-ERD frames LLM self-alignment as latent structure mining via a Variational Logic Potential and Multi-Agent Value Decomposition to provide granular, logic-consistent supervision.
MO-GRPO: Mitigating reward hacking of group relative policy optimization on multi-objective problems
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Reshaping outcome rewards, process signals, and rollout comparability in GRPO raises strict compile-and-semantic accuracy in agentic code repair from 0.385 to 0.535 under weak feedback.
Compact 0.8B-7B models for bidirectional Japanese-English translation outperform large multilingual models on real-world domain benchmarks.
citing papers explorer
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LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition
LC-ERD frames LLM self-alignment as latent structure mining via a Variational Logic Potential and Multi-Agent Value Decomposition to provide granular, logic-consistent supervision.
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Signal Reshaping for GRPO in Weak-Feedback Agentic Code Repair
Reshaping outcome rewards, process signals, and rollout comparability in GRPO raises strict compile-and-semantic accuracy in agentic code repair from 0.385 to 0.535 under weak feedback.
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CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation
Compact 0.8B-7B models for bidirectional Japanese-English translation outperform large multilingual models on real-world domain benchmarks.