Coding agents resend a growing context on every model call, and context policies are usually judged by the prompt tokens they save. Executed work also depends on call count and prefix reuse: a caching runtime prefills only the tokens after the longest cached prefix. A shorter prompt can therefore cost more if it rewrit...
Zhong-Ming Yu, Yi-Tong Ma, Heng-Jia Yu et al.· 0 citations
CAKE, a compiler-agent co-design in which agents author CAKE IR, a typed, hardware-explicit schedule representation, exposes warp roles, memory movement, synchronization, and pipelines while supporting verification, cost modeling, and localized diagnostics.
Zihao Ye, Yingyi Huang, H. Jin et al.· 4 citations
Together, these results support multi-view repository-context serving with explicit, operation-specific validity boundaries with quality-cost frontiers across the repository-context lifecycle.
CHORUS is presented, a post-training framework that pushes performance beyond what a conventional supervised fine-tuning (SFT)-to-reinforcement learning (RL) pipeline achieves, and consolidates the resulting specialists into a single 4B model.
He-Jia Zhang, Sheng Lu, Zhongming Yu et al.· 0 citations
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