Coding agents solve repository issues through long sequences of exploration, editing, and validation. These trajectories are increasingly used as post-training data, so how they are collected shapes w
SWE-Trail improves trajectory collection for coding agents by using past rollouts to guide exploration without exposing history to the agent, yielding better-trained student models.
Coding agents solve repository issues through long sequences of exploration, editing, and validation. These trajectories are increasingly used as post-training data, so how they are collected shapes what the trained model learns. A common approach is to sample multiple trajectories independently for each issue and then select or curate them. However, as more trajectories are sampled independently, later trajectories become increasingly redundant, even though earlier trajectories could guide where subsequent collection effort should be spent. A natural way to use this history is to expose it to the coding agent as advice. But training on such trajectories can make the model rely on advice…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
SWE-Trail: History-Guided Trajectory Collection for Coding Agent Training was first seen on Hugging Face · Daily papers on Nov 3, 2026. Since then it has appeared in 10 checks on 2 different days. Its best position was #2 of 30, reached on Nov 4, 05:28 UTC. It dropped off the list after Nov 4, 07:28 UTC.
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Not at the moment. It was last on the list on Nov 4, 07:28 UTC, after 2 days of trending.
#2 on Hugging Face · Daily papers, on Nov 4, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 3, 2026 and has been on the list on 2 days (10 checks) since.