Xtra-Computing/XtraGPT-7B
Xtra-Computing/XtraGPT-7B is a 7.6 billion parameter open-source Large Language Model fine-tuned for human-AI collaborative academic paper revision. Based on Qwen/Qwen2.5-7B-Instruct, it is designed to understand full paper context and execute criteria-guided revision instructions. This model excels at providing controllable and context-aware improvements across 20 academic writing criteria, supporting an iterative human-AI workflow. It is specifically optimized for enhancing the quality and consistency of research papers.
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XtraGPT-7B: Context-Aware Academic Paper Revision
XtraGPT-7B is a 7.6 billion parameter model from the XtraGPT family, specifically engineered for human-AI collaborative academic paper revision. Unlike general-purpose LLMs, XtraGPT-7B is fine-tuned to deeply understand the full context of a research paper, ensuring revisions maintain consistency with the global narrative. It processes specific, criteria-guided revision instructions, making it highly controllable for authors.
Key Capabilities
- Context-Aware Revision: Processes entire paper content to ensure suggested revisions are consistent and relevant to the overall document.
- Controllable Output: Follows precise user instructions based on 20 academic writing criteria across six paper sections (e.g., Abstract, Introduction).
- Human-AI Collaboration: Designed to integrate seamlessly into an iterative workflow where human authors retain creative control over the revision process.
- Specialized Training: Trained on a high-quality dataset of 140,000 instruction-revision pairs derived from top-tier conference papers (ICLR).
Good For
- Researchers and academics seeking AI assistance for refining and improving their scientific manuscripts.
- Automating specific, criteria-based edits while maintaining the paper's overall coherence.
- Integrating AI into academic writing workflows for enhanced productivity and quality control.