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arXiv · 2505.14376

Graph-Guided Passage Retrieval for Author-Centric Structured Feedback

Maitreya Prafulla Chitale·Ketaki Mangesh Shetye·Harshit Gupta·Manav Chaudhary·Manish Shrivastava·Vasudeva Varma
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Abstract

Obtaining high-quality, pre-submission feedback is a critical bottleneck in the academic publication lifecycle for researchers. We introduce AutoRev, an automated author-centric feedback system that generates structured, actionable guidance prior to formal peer review. AutoRev employs a graph-based retrieval-augmented generation framework that models each paper as a hierarchical document graph, integrating textual and structural representations to retrieve salient content efficiently. By leveraging graph-based passage retrieval, AutoRev substantially reduces LLM input context length, leading to higher-quality feedback generation. Experimental results demonstrate that AutoRev significantly outperforms baselines across multiple automatic evaluation metrics, while achieving strong performance in human evaluations. Code will be released upon acceptance.

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Maitreya Prafulla Chitale, Ketaki Mangesh Shetye, Harshit Gupta, Manav Chaudhary, Manish Shrivastava, Vasudeva Varma. 2025-05-20. Graph-Guided Passage Retrieval for Author-Centric Structured Feedback. https://arxiv.org/abs/2505.14376

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