TL;DR
XtraGPT is an open-source, context-aware LLM framework designed for high-quality academic paper revision through human-AI collaboration, addressing the limitations of existing scientific writing tools.
Contribution
It introduces a novel human-AI collaboration framework with criteria-guided intent alignment and context modeling, and provides a fine-tuned LLM suite for academic revision.
Findings
XtraGPT outperforms baseline models in scientific draft improvement.
Automated and human evaluations confirm XtraGPT's effectiveness.
The dataset of 7,000 papers and 140,000 instruction-response pairs supports realistic scientific revisions.
Abstract
Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality scientific writing. Most existing systems are designed for general-purpose scientific text generation and fail to meet the sophisticated demands of research communication beyond surface-level polishing, for example, maintaining conceptual coherence across sections. Furthermore, academic writing is inherently iterative and revision-driven, a process that is not well supported by direct prompting-based paradigms. To address these scenarios, we propose a human-AI collaboration framework for academic paper revision, centered on criteria-guided intent alignment and context-aware modeling. To validate the framework, we curate a dataset of 7,000 research papers from top-tier venues, annotated with 140,000 instruction--response pairs that reflect…
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