3 papers
cs.CL2026
SWE-Pruner Pro: The Coder LLM Already Knows What to Prune
Yuhang Wang, Yuling Shi, Shaoqiu Zhang +6
Pruning long context for coding agents has been a vital technology for efficient context management. While existing context pruning methods such as SWE-Pruner realize this by attac…
cs.SE2026
SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
Yuhang Wang, Yuling Shi, Mo Yang +7
LLM agents have demonstrated remarkable capabilities in software development, but their performance is hampered by long interaction contexts, which incur high API costs and latency…
cs.AI2026
GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts
Wenhao Zeng, Xuteng Zhang, Yuling Shi +4
Large Reasoning Models (LRMs) achieve remarkable performance by explicitly generating multi-step chains of thought, but this capability incurs substantial inference latency and com…