student_partial_sciworld

Partial SciWorld trajectories: Qwen3-1.7B (base) acting for its first 5 turns on the 2,120-task training split. These are the student prefixes an online-ROSE run sees before the teacher takes over — captured separately so the take-over point can be studied, or teacher continuations generated offline.

What is here

rows	2,120 (one per training task)
file	student_partial_sciworld.jsonl (11.4 MB)
model	Qwen/Qwen3-1.7B, untrained base — the starting point of our ROSE/OPD runs
turns	5 (mean 4.96; a few episodes end early)
sampling	temperature 1.0, max_new_tokens 512, context 16384
mean score	0.0352

Sampling matches what the student does inside the online-ROSE loop, so these prefixes are distributionally the same as the ones the teacher continues during training.

Schema

{
  "item_id": "sciworld_0",
  "task": "boil",
  "var": 0,
  "score": 0.0,          // ScienceWorld completion in [0,1] after 5 turns
  "success": 0,          // score == 1
  "rounds": 5,
  "conversations": [     // system + 24-action instruction + ack, then obs/action pairs
    {"role": "user", "content": "You are an agent for science world. ..."},
    {"role": "assistant", "content": "OK. I'll follow your instructions ..."},
    {"role": "user", "content": "<observation>"},
    {"role": "assistant", "content": "Thought: ...\nAction: ..."}
  ]
}

conversations is the full AgentGym-protocol dialogue, ready to re-render with any chat template.

Why 5 turns

Five turns is where online ROSE cuts. At that point the student has explored but has essentially completed nothing — mean score 0.0352, versus 0.0479 when the same base model runs the full 20 turns. The take-over lands after the student has committed to an approach but before the episode is decided.

For reference, on the same environment (200 held-out tasks, ≤20 turns, greedy):

	Score	Success	Pass(>0)
Qwen3-1.7B base	0.0479	0.0000	0.1650
SFT on Qwen3-32B trajectories	0.2077	0.0450	0.4100
online ROSE (5 student + 5 teacher)	0.3127	0.0600	0.6600
Qwen3-32B teacher	0.4346	0.1100	0.9350

Environment

ScienceWorld via the AgentGym protocol. Tasks are (task_type, variation) pairs with seven variation families excluded (5-1 5-2 9-1 9-2 9-3 10-1 10-2), giving 4,639 games total; this split holds 2,120 of them. The prompt is the standard 24-action REACT instruction, and actions are parsed from the first non-empty line after Action:.

Scores are ScienceWorld's own completion signal, not a learned reward.