MemoryWalker: Stop Training Agents on Contexts They Never Saw
cs.LG, cs.CL
Submitted: 2026-09-01
Updated: 2026-09-01
Code: https://github.com/jiangxinke/Agentic-RAG-R1
Terminology
Sources
- Reweighted Wake-Sleep
- CIG: Measuring Conversational Information Gain in Deliberative Dialogues with Semantic Memory Dynamics
- REDSearcher: A Scalable and Cost-Efficient Framework for Long-Horizon Search Agents
- Understanding the planning of LLM agents: A survey
- Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
- Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation
- Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
- Lost in the Middle: How Language Models Use Long Contexts
- MemGPT: Towards LLMs as Operating Systems
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Deep Research: A Systematic Survey
- AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities
- Memex(RL): Scaling Long-Horizon LLM Agents via Indexed Experience Memory
- WideSearch: Benchmarking Agentic Broad Info-Seeking
- A Survey of LLM-based Deep Search Agents: Paradigm, Optimization, Evaluation, and Challenges
- Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
- AgentFold: Long-Horizon Web Agents with Proactive Context Management
- StackPlanner: A Centralized Hierarchical Multi-Agent System with Task-Experience Memory Management
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