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[2602.14367] InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem
Summary
The paper introduces InnoEval, a framework for evaluating research ideas using knowledge-grounded, multi-perspective reasoning, addressing limitations in current evaluation methods.
Why It Matters
As scientific idea production accelerates, effective evaluation methods are crucial for ensuring quality and relevance. InnoEval aims to enhance evaluation processes by incorporating diverse perspectives and grounding assessments in robust knowledge, which is essential for advancing research integrity and innovation.
Key Takeaways
- InnoEval addresses the shortcomings of existing research idea evaluation methods.
- The framework utilizes a deep knowledge search engine for dynamic evidence retrieval.
- It incorporates a multi-dimensional evaluation approach with diverse reviewers.
- Experiments show InnoEval's effectiveness in aligning with human expert judgments.
- The framework is benchmarked against comprehensive datasets from peer-reviewed submissions.
Computer Science > Computation and Language arXiv:2602.14367 (cs) [Submitted on 16 Feb 2026] Title:InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem Authors:Shuofei Qiao, Yunxiang Wei, Xuehai Wang, Bin Wu, Boyang Xue, Ningyu Zhang, Hossein A. Rahmani, Yanshan Wang, Qiang Zhang, Keyan Ding, Jeff Z. Pan, Huajun Chen, Emine Yilmaz View a PDF of the paper titled InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem, by Shuofei Qiao and 12 other authors View PDF HTML (experimental) Abstract:The rapid evolution of Large Language Models has catalyzed a surge in scientific idea production, yet this leap has not been accompanied by a matching advance in idea evaluation. The fundamental nature of scientific evaluation needs knowledgeable grounding, collective deliberation, and multi-criteria decision-making. However, existing idea evaluation methods often suffer from narrow knowledge horizons, flattened evaluation dimensions, and the inherent bias in LLM-as-a-Judge. To address these, we regard idea evaluation as a knowledge-grounded, multi-perspective reasoning problem and introduce InnoEval, a deep innovation evaluation framework designed to emulate human-level idea assessment. We apply a heterogeneous deep knowledge search engine that retrieves and grounds dynamic evidence from diverse online sources. We further achieve review consensus with an innovation review board containing reviewers...
