---
license: apache-2.0
language:
- en
task_categories:
- other
tags:
- web-agent
- browser-use
- agent-trajectories
- webvoyager
- gaia
- qwen
- multimodal
size_categories:
- n<1K
configs:
- config_name: default
  data_files: metadata.jsonl
---

# WebVoyager + GAIA Agent Trajectories (Qwen3.5-Omni)

Full browser-agent trajectories for **733 tasks** (643 [WebVoyager](https://github.com/MinorJerry/WebVoyager) + 90 GAIA-web), produced by a [browser-use](https://github.com/browser-use/browser-use) agent driven by **`qwen3.5-omni-plus-2026-03-15`** (multimodal, via Alibaba DashScope), run in a real **headed** browser. Every step records the exact LLM context (including the screenshot the model saw) and the action taken, plus a reference-grounded success verdict.

## Results

Judged by the WebVoyager reference-grounded multimodal judge (`qwen3.5-omni-plus-2026-03-15`). Each task is the **better of two independent runs** (success-preferring merge — keep a run's trajectory if it succeeded, otherwise take the other):

| split | success | rate |
|---|---|---|
| **overall** | 511 / 733 | **69.7%** |
| WebVoyager | 457 / 643 | 71.1% |
| GAIA-web | 54 / 90 | 60.0% |

## Layout

```
metadata.jsonl              one row per task (index; loaded by `load_dataset`)
run_summary.json            run + merge provenance and success counts
data/<source>__<id>/
  meta.json                 task id/site/source, question, start_url, reference answer, status, final answer
  tool_schema.json          structured-output (tool) schema used each step
  history.json              browser-use AgentHistoryList (structured actions/states)
  webvoyager_eval.json      success verdict + judge reasoning
  step_001/
    messages.json           EXACT LLM request context: [system, user(<agent_history> text, "Current screenshot:", image_url base64)]
    output.json             the LLM output for that step (thinking + action taken)
    screenshot.jpg          the page at the start of the step
    state.json              url + title at the start of the step
  step_002/ ...
```

`messages.json` is the verbatim chat-completion request (OpenAI-compatible) the agent sent that step — system prompt + a user message whose content is the agent history text, the literal `Current screenshot:`, and the screenshot as an inline base64 image (downscaled to 1280×720). It is preserved unchanged so a trajectory can be replayed/scored fully offline.

## `metadata.jsonl` columns

`id, source (webvoyager|gaia), site, question, start_url, reference_answer, reference_type, agent_answer, status (completed|timeout|error), num_steps, success (bool, judge verdict), judge_reasoning, used_reference, trajectory_dir`

## Usage

```python
from datasets import load_dataset
meta = load_dataset("shiqihe/WebVoyager-Trajectories-Qwen3.5-Omni")["train"]   # the 733-task index
# full per-step trajectories are the files under data/<trajectory_dir>/
```

## Notes

- Reference answers: WebVoyager's `reference_answer.json` (per site) and GAIA's inline `Final answer`; both are embedded per task and used to ground the success judge.
- Generated with browser-use; structured output via `response_format` json_schema; one screenshot per step (vision on).