Context Pruning for Coding Agents via Multi-Rubric Latent Reasoning
cs.AI, cs.CL
Submitted: 2026-05-14
Updated: 2026-09-26
Terminology
Sources
- Lost in the Middle: How Language Models Use Long Contexts
- Retrieval-Augmented Generation for Large Language Models: A Survey
- LongCodeZip: Compress Long Context for Code Language Models
- UniXcoder: Unified Cross-Modal Pre-training for Code Representation
- Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
- SWE-QA: Can Language Models Answer Repository-level Code Questions?
- LongCodeBench: Evaluating Coding LLMs at 1M Context Windows
- RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems
- Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
- Scaling LLM Multi-turn RL with End-to-end Summarization-based Context Management
- Scaling Long-Horizon LLM Agent via Context-Folding
- The Complexity Trap: Simple Observation Masking Is as Efficient as LLM Summarization for Agent Context Management
- ACON: Optimizing Context Compression for Long-horizon LLM Agents
- AgentFold: Long-Horizon Web Agents with Proactive Context Management
- COMPASS: Enhancing Agent Long-Horizon Reasoning with Evolving Context
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