Diffusion multimodal large language models (dMLLMs) frequently produce long-form outputs marred by semantic drift and repetition, with quality generally degrading as output length increases. We identify two structural deficiencies in existing decoding methods as primary drivers of these failures: confidence-based scori...
Yikai Zhao, Qiyan Zhao, Jia-Quan Zhang et al.· 0 citations
Training capable coding agents via reinforcement learning (RL) requires diverse tasks with reliable verifiers. Open-source codebases offer a rich source of such tasks, while existing methods typically rely on development artifacts such as issues and commits, limiting the range of tasks that can be extracted. To better...
Bo-Wen Ye, Lei Li, Shi-Cheng Li et al.· 0 citations
This work presents TRACE (TRajectory Attribution for Automated Context Engineering), an automated feedback loop that mines historical agent trajectories to diagnose and remediate context failures, showing that over 80% of context-layer failures can be automatically diagnosed and remediated by mining historical trajecto...