This paper presents ContextSniper, a token-efficient code memory layer that sits between a host coding agent and a repository that retrieves candidate code and runtime evidence, ranks it with hybrid retrieval signals, filters long outputs through an intention-aware context gate, and returns compact evidence packets while preserving recoverable source context outside the prompt.
A controlled seed-intervention pilot finds that retrieval-derived initial context yields higher file F1 with less post-seed exploration than random non-gold context, while oracle gold context shows substantial remaining headroom.
The ORCA-bench benchmark is introduced, a benchmark that puts general-purpose coding agents in a production-fidelity oncall setting and is a lower bound on the engineering investment required before frontier coding agents can be safely entrusted with production reliability.
Albert Gong, Kyuseong Choi, Abhineet Agarwal et al.· arXiv.org· 1 citation
ACToR identifies critical tokens during generation and triggers targeted retrieval on demand to provide repository context at these decisive positions, and designs a position-aware weighting method for dense retrievers to prioritize context that is more informative for generation.
Ke-Feng Duan, De-Wu Zheng, Yan-Lin Wang et al.· 0 citations
OwlPath is presented, an OWL2 reasoning layer atop CodeGraph, a widely used code intelligence platform with 500K+ GitHub stars, offering a unified CLI for structural code retrieval, with lossless knowledge compression.
Bo Zhang, Renke Pan, Huan Chen et al.· arXiv.org· 0 citations
This work presents Evolutionary Self-Debugging Agents (ESDA), which mines tool traces into structured failure signatures and uses them to maintain a strategy bank of reusable debugging policies, and analyze transfer across languages and build systems and finds that mining failure signatures yields consistent gains unde...
Shuang Cao, Rui Li· Proceedings of the 32nd ACM...· 0 citations
These results show that MegaMem supports ultra-large persistent memory while preserving strong answer accuracy under a bounded generation context, and provides a practical path toward accurate retrieval over memories ranging from hundreds of millions to one billion tokens.
Xin-Yuan Song, Bo-Wen Zhu, H. Haque et al.· 0 citations
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