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README.md
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README.md
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---
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license: apache-2.0
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base_model:
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- Qwen/Qwen3-8B
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language:
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- en
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library_name: transformers
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license: mit
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tags:
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- LLM
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pipeline_tag: text-generation
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---
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# 🔍 WebExplorer-8B
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<!-- [](https://huggingface.co/WebExplorer-8B)
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[](https://arxiv.org/abs/xxxx.xxxxx) -->
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A state-of-the-art 8B parameter web agent model designed for complex information-seeking tasks and long-horizon reasoning.
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## 🌟 Overview
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WebExplorer-8B is an advanced web navigation agent trained on **WebExplorer**-QA. The model demonstrates exceptional performance on challenging information-seeking benchmarks while maintaining efficiency with only 8 billion parameters.
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## ✨ Key Features
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- 🌐 **Long-horizon Reasoning**: Supports up to 128K context length and 100 tool calling turns
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- 🛠️ **Tool Utilization**: Masters search and browse functionalities
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- 🏆 **State-of-the-art Performance**: Achieves best-in-class results among models under 10B parameters
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## 🏗️ Model Architecture
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Built on Qwen3-8B base model and trained through a two-phase approach:
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1. **Supervised Fine-tuning (SFT)**: Cold-start initialization with high-quality trajectories
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2. **Reinforcement Learning (RL)**: Enhanced using GRPO algorithm with progressive context expansion
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## 📊 Performance
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WebExplorer-8B achieves state-of-the-art performance across multiple information-seeking benchmarks:
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| Benchmark | Score |
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|-----------|-------|
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| BrowseComp-en | **15.7** |
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| BrowseComp-zh | **32.0** |
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| GAIA | **50.0** |
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| WebWalkerQA | **62.7** |
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| FRAMES | **75.7** |
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| XBench-DeepSearch | **53.7** |
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| HLE | **17.3** |
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## 🛠️ Tool Schema
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WebExplorer-8B supports two tools for web interaction:
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### 1. Browse Tool
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```json
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{
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"name": "browse",
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"type": "function",
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"description": "Extract specific information from a webpage",
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"parameters": {
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"type": "object",
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"properties": {
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"url": {
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"type": "string",
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"description": "Target URL to browse. The webpage content will be processed by the LLM for information extraction."
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},
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"query": {
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"type": "string",
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"description": "Specific query about the webpage content. The LLM will analyze the content to answer this query."
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}
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},
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"required": ["url", "query"]
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}
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}
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```
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### 2. Search Tool
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```json
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{
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"name": "search",
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"type": "function",
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"description": "Perform web search queries",
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"parameters": {
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"type": "object",
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"properties": {
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"queries": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "List of search queries. Returns search results containing title, URL, and snippet for each query."
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}
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},
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"required": ["queries"]
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}
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}
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```
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