Any tool to get accepted conference papers sorted by citation count? [D]

· Source: Machine Learning · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Novice, quick

Summary

The challenge of finding a tool to sort accepted conference papers by citation count, such as for NeurIPS 2025, is noted as surprisingly difficult. Semantic Scholar offers a direct method to sort papers by total citations for specific venues and years, exemplified by a URL for NeurIPS 2024-2026. However, a significant caveat is that citation counts are a poor signal for very recent papers, like those 6 months out from NeurIPS 2025, as good papers require time to accumulate citations. PaperDigest.org is also mentioned as covering hundreds of conferences. The current optimal solution appears to be a combination of Semantic Scholar and the OpenReview API, with the potential to build a small custom tool using platforms like Runable to automate the process of pulling papers and sorting them by citation data.

Key takeaway

For research scientists or AI engineers tracking emerging work from recent conferences like NeurIPS 2025, relying solely on citation counts for paper evaluation is premature. You should instead combine Semantic Scholar for broader citation trends with the OpenReview API to access accepted papers. Consider developing a lightweight custom tool, perhaps with a platform like Runable, to automate this data integration and sorting, providing a more current and comprehensive view of impactful research despite the inherent citation lag.

Key insights

Sorting recent conference papers by citation count is challenging, requiring combined tools or custom solutions due to citation lag.

Principles

Method

Combine Semantic Scholar for citation data with OpenReview API for accepted papers, then sort programmatically.

In practice

Topics

Best for: AI Scientist, Research Scientist, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning.