CalibAdv calibrates advantages in GRPO by downscaling negative signals from incorrect final answers using intermediate step correctness and rebalancing answer-level advantages, yielding better performance and training stability on multiple models and benchmarks.
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
MASS-RAG uses distinct agents for evidence summarization, extraction, and reasoning, then synthesizes their outputs to improve answer quality over standard RAG baselines on four benchmarks, especially when evidence is distributed.
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Negative Advantage Is a Double-Edged Sword: Calibrating Advantage in GRPO for Deep Search
CalibAdv calibrates advantages in GRPO by downscaling negative signals from incorrect final answers using intermediate step correctness and rebalancing answer-level advantages, yielding better performance and training stability on multiple models and benchmarks.
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MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation
MASS-RAG uses distinct agents for evidence summarization, extraction, and reasoning, then synthesizes their outputs to improve answer quality over standard RAG baselines on four benchmarks, especially when evidence is distributed.