🧑‍🔬 Ameya Prabhu

🏛️ Affiliations

🎓University of TübingenTübingen · Germany2024–2026 · 23 paperscurrent🎓Tübingen AI CenterTübingen · Germany2024–2026 · 15 paperscurrent🎓University of OxfordOxford · United Kingdom2019–2024 · 17 papers🎓International Institute of Information Technology, HyderabadHyderabad · India2015–2018 · 8 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Inverse Scaling: When Bigger Isn't Better (2023 · 105 citations)
   Scaling laws predict that larger language models steadily lower training loss and usually improve on downstream tasks.
2. Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry (2024 · 7 citations)
   Automated proving of olympiad geometry is often treated as a milestone for machine reasoning. AlphaGeometry is a neuro-symbolic system trained on 100 million synthetic proofs. It solved 25 of the 30 problems in the IMO-AG-30 benchmark, while the Wu's method baseline reported alongside it managed only ten. The authors…

All works

7 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 105 citations
2. A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility ↗arXiv:2504.07086 · no summary yetAndreas Hochlehnert et al.2025 · 36 citations
3. CiteME: Can Language Models Accurately Cite Scientific Claims? ↗arXiv:2407.12861 · no summary yetOri Press et al.2024 · 25 citations
4. Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO GeometryarXiv:2404.06405Shiven Sinha, Ameya Prabhu, Ponnurangam Kumaraguru, et al.2024 · 7 citations
5. A Practitioner's Guide to Continual Multimodal Pretraining ↗arXiv (Cornell University) · no summary yetKarsten Roth et al.2024 · 4 citations
6. A Practitioner's Guide to Real-World Continual Multimodal Pretraining ↗neural information processing systems · no summary yetVishaal Udandarao et al.2024 · 4 citations
7. Round-Trip Translation Reveals What Frontier Multilingual Benchmarks Miss ↗arXiv:2604.12911 · no summary yetRonald Skorobogat, Ameya Prabhu, Matthias Bethge2026 · 2 citations

🤝 Co-authors here

6 co-authors with a page, the most papers together first.

• Aaron Mueller
• Alexis Ross
• Alicia Parrish
• Alisa Liu
• Michael Pieler
• Ponnurangam Kumaraguru

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Nature
• neural information processing systems

🔗 Cited by

Papers of our library cite their works 360 times (of the 149,439 papers whose bibliographies we read); 86 citing papers with a page here →.

Updated 30 October 2026

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