arXiv Machine Learning
IRAH: Hierarchical Agentic Tree Search for Retrieval Pipeline Optimization
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Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents
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arXiv Machine Learning
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Strategy Accumulation and Guided Execution for Automated LLM Fine-Tuning
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GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG
arXiv:2607. 21324v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems increasingly employ multiple LLM agents.
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Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents
arXiv:2610.16998v1 Announce Type: new Abstract: Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-sourc...
arXiv Machine Learning
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DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution
arXiv:2607. 26722v1 Announce Type: cross Abstract: Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort.
arXiv AI
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Simple Baselines are Competitive with Code Evolution
arXiv:2602.16805v2 Announce Type: replace Abstract: Code evolution is a family of techniques that rely on large language models to search through possible computer programs by evolving existing code....