data agents 1finetuning 1heterogeneous data environments 1in-context learning 1monte carlo tree search 1trajectory synthesis 1
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cs.AI2026
Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale
Ziting Wang, Yin Li, Zuhao Yang +3
The paper presents TOFFEE, a system that uses Monte Carlo Tree Search and learned cost models to automatically generate data‑agent interaction trajectories for diverse data environ…
cs.AI2026
ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair
Chiwang Luk, Matin Mohammad Najafi, Zhifeng Jia +6
Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long terminal outputs where usefu…