99 lines
2.9 KiB
Markdown
99 lines
2.9 KiB
Markdown
# BrowseComp
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## Overview
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BrowseComp is an OpenAI benchmark for evaluating browsing and search agents. It contains 1,266 hard-to-find, fact-seeking questions with short, verifiable answers. EvalScope loads the mirrored dataset from ModelScope (`evalscope/browse_comp`).
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## Task Description
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- **Task Type**: Search-agent factual question answering
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- **Input**: Challenging natural-language question that generally requires persistent web browsing
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- **Output**: Explanation, exact answer, and confidence
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- **Grading**: LLM judge compares the final answer against the reference answer
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## Key Features
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- Tests persistence, creative search, and multi-hop evidence gathering
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- Uses short answers to keep grading tractable
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- Official data is distributed as encrypted CSV rows and decrypted at evaluation time
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- Classified as an Agent benchmark and compatible with EvalScope agent loop modes
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- Supports single-turn model evaluation by default and native/external agent execution when `TaskConfig.agent_config` is provided
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## Evaluation Notes
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- Default evaluation loads `evalscope/browse_comp` from ModelScope through the standard EvalScope dataset loader.
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- Use `TaskConfig.agent_config` to evaluate BrowseComp with EvalScope agent loop capabilities such as native tool-use or external agent runners.
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- The primary metric is `is_correct`; `is_incorrect` is also reported.
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- LLM judge is enabled by default. `JudgeStrategy.RULE` falls back to normalized exact match.
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `browsecomp` |
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| **Dataset ID** | [evalscope/browse_comp](https://modelscope.cn/datasets/evalscope/browse_comp/summary) |
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| **Paper** | [Paper](https://arxiv.org/abs/2504.12516) |
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| **Tags** | `Agent`, `Knowledge`, `QA` |
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| **Metrics** | `is_correct`, `is_incorrect` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `test` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 1,266 |
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| Prompt Length (Mean) | 811.02 chars |
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| Prompt Length (Min/Max) | 424 / 2219 chars |
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## Sample Example
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*Sample example not available.*
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## Prompt Template
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**Prompt Template:**
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```text
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{question}
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Your response should be in the following format:
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Explanation: {{your explanation for your final answer}}
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Exact Answer: {{your succinct, final answer}}
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Confidence: {{your confidence score between 0% and 100% for your answer}}
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```
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets browsecomp \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['browsecomp'],
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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