Datasets:
Clarification on Context Resets and Switches in SFT Data Collection
Hi, thanks for sharing this work!
I noticed that the paper reports 64,505 SFT trajectories collected from 1,648 environments, and mentions that a single task-level rollout can be split into multiple trajectories due to Claude Code's context resets or switches.
Could you provide some additional statistics on this process?
How many independent task-level rollouts were conducted in total?
On average, how many context resets and context switches occurred per rollout?
What is the average number of SFT trajectory segments generated from a single rollout?
These details would help clarify the effective scale and diversity of the SFT data.
Thanks!
Thank you for your interest and for raising these questions!
How many independent task-level rollouts were conducted in total?
We conducted 1,648 independent task-level rollouts, one for each ProgramGym task.
On average, how many context resets and context switches occurred per rollout?
On average, there were approximately 38.1 context resets or switches per rollout (combined). These events mainly fall into two categories:
- System prompt updates: Claude Code updates its system prompt during execution (e.g., when workspace files change), while preserving the conversation history.
- Context compaction: When the context becomes too long, Claude Code automatically compacts it, modifying the preceding conversation history.
In our observations, system prompt updates occurred approximately every 4 steps, while context compaction occurred roughly every 100 steps.
What is the average number of SFT trajectory segments generated from a single rollout?
Each rollout generated approximately 39.1 SFT trajectory segments on average (64,505 segments across 1,648 rollouts).
Each segment contains approximately 51 steps on average, but only about 4 steps provide new SFT training targets. The remaining steps are included as historical context and have already appeared as training targets in preceding segments.
Therefore, although our dataset contains 64,505 SFT trajectories, these segments are not independent task-level executions. Rather, they are overlapping training segments derived from 1,648 independent rollouts, with most segmentation boundaries arising from Claude Code's frequent system prompt updates.