MetaRAG: Belief-Action Aligned Policy Optimization for Agentic RAG
cs.AI
Submitted: 2026-08-25
Updated: 2026-08-25
Terminology
Sources
- Query-Level Uncertainty in Large Language Models
- BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent
- Training Verifiers to Solve Math Word Problems
- Language Model Cascades
- Group-in-Group Policy Optimization for LLM Agent Training
- DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
- Language Model Cascades: Token-level uncertainty and beyond
- Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps
- Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
- TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
- Language Models (Mostly) Know What They Know
- Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
- Teaching Models to Express Their Uncertainty in Words
- When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories
- Measuring and Narrowing the Compositionality Gap in Language Models
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- ZeroSearch: Incentivize the Search Capability of LLMs without Searching
- HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
- ReAct: Synergizing Reasoning and Acting in Language Models
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