PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents

arXiv:2609.06702 · cs.CL · Submitted 2026-09-06 · Read on arXiv

cs.CL

Submitted: 2026-09-06

Updated: 2026-09-26

Code: https://github.com/BytedTsinghua-SIA/MemAgent

Project page: https://cuhk-parser.github.io

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 19× in this paper · explained in 1 episode
• Actor — 14× in this paper · explained in 3 episodes
• EMMA — 9× in this paper · explained in 2 episodes
• Reinforcement Learning — 9× in this paper · explained in 4 episodes
• KV cache — 5× in this paper · explained in 3 episodes
• Member of the European Parliament — 5× in this paper
• Thinking mode — 5× in this paper · explained in 2 episodes
• Sparse Attention — 4× in this paper · explained in 5 episodes
• Agentic Search — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Abstention — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• GRPO — 2× in this paper · explained in 6 episodes
• In International Conference on Machine Learning — 2× in this paper
• KL Regularization — 2× in this paper · explained in 2 episodes
• Multi-agent Collaboration — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• KV cache reuse — 1× in this paper · explained in 2 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Perplexity — 1× in this paper · explained in 3 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading
• Extending Context Window of Large Language Models via Positional Interpolation
• Multi-Agent Collaboration via Evolving Orchestration
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
• ToM: Leveraging Tree-oriented MapReduce for Long-Context Reasoning in Large Language Models
• Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
• RULER: What's the Real Context Size of Your Long-Context Language Models?
• OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
• FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
• Kimi K3: Open Frontier Intelligence
• A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
• Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus Interaction
• Block-Attention for Efficient Prefilling
• Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
• MiniMax Sparse Attention
• Parallel Context Windows for Large Language Models
• GrepSeek: Training Search Agents for Direct Corpus Interaction
• Is Grep All You Need? How Agent Harnesses Reshape Agentic Search
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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