Hugging Face Trending Papers August 5, 2026

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

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Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon agentic workflows. Existing long-context corpora, however, are dominated by books, academic articles, and code repositories, which are finite resources and often scarce in long-distance dependencies.

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arXiv AI

Aug 6

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

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Related stories

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding

ACC: Compiling Agent Trajectories for Long-Context Training

Diagnosing Knowledge Gaps in LLM Tool Use: An Agentic Benchmark for Novel API Acquisition

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Learning from Execution: Self-Evolving Memory for Private-Library Code Generation