SWE-TRACE optimizes long-horizon SWE agents via token-efficient SFT distillation, rubric-augmented process reward models in RL, and heuristic test-time scaling, yielding higher benchmark resolution rates with reduced tokens and latency.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
SWE-TRACE: Optimizing Long-Horizon SWE Agents Through Rubric Process Reward Models and Heuristic Test-Time Scaling
SWE-TRACE optimizes long-horizon SWE agents via token-efficient SFT distillation, rubric-augmented process reward models in RL, and heuristic test-time scaling, yielding higher benchmark resolution rates with reduced tokens and latency.