---
title: "Sanmi Koyejo — all works — Elamur Research"
description: "All 27 works of Sanmi Koyejo in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/sanmi-koyejo/works/"
---
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# Sanmi Koyejo — all works

27 works · [← Sanmi Koyejo](https://md.research.elamur.ai/free/en/authors/sanmi-koyejo/)

1. **[Examples are not enough, learn to criticize! Criticism for Interpretability ↗](https://openalex.org/W2551974706) neural information processing systems · no summary yet**Been Kim, Rajiv Khanna, Sanmi Koyejo*2016 · 527 citations*
2. **[Are Emergent Abilities of Large Language Models a Mirage?](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 342 citations*
3. **[Rethinking machine unlearning for large language models ↗](https://doi.org/10.1038/s42256-025-00985-0) Nature Machine Intelligence · no summary yet**Sijia Liu et al.*2025 · 197 citations*
4. **[Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data ↗](https://arxiv.org/abs/2404.01413) arXiv (Cornell University) · no summary yet**Matthias Gerstgrasser et al.*2024 · 44 citations*
5. **[Advancing science- and evidence-based AI policy ↗](https://doi.org/10.1126/science.adu8449) Science · no summary yet**Rishi Bommasani et al.*2025 · 25 citations*
6. **[The Leaderboard Illusion](https://md.research.elamur.ai/free/en/papers/singh-2025-leaderboard-illusion/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivalika Singh, Yiyang Nan, Alex Wang, et al.*2025 · 22 citations*
7. **[Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research ↗](https://doi.org/10.52202/085713-2990) neural information processing systems · no summary yet**A. Feder Cooper et al.*2025 · 17 citations*
8. **[Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4](https://md.research.elamur.ai/free/en/papers/aniva-2024-pantograph-machine-machine-interaction-interface/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Leni Aniva, Chuyue Sun, Brando Miranda, et al.*2024 · 14 citations*
9. **[Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice ↗](https://doi.org/10.2139/ssrn.5060253) SSRN Electronic Journal · no summary yet**A. Feder Cooper et al.*2025 · 12 citations*
10. **[End-to-End Test-Time Training for Long Context ↗](https://arxiv.org/abs/2512.23675) arXiv (Cornell University) · no summary yet**Arnuv Tandon et al.*2025 · 10 citations*
11. **[Extracting books from production language models ↗](https://arxiv.org/abs/2601.02671) arXiv (Cornell University) · no summary yet**Ahmed Ahmed et al.*2026 · 8 citations*
12. **[UQ: Assessing Language Models on Unsolved Questions ↗](https://arxiv.org/abs/2508.17580) arXiv (Cornell University) · no summary yet**Nie, Fan et al.*2025 · 6 citations*
13. [**Learning to (Learn at Test Time) arXiv:2310.13807**Yu Sun, Xinhao Li, Karan Dalal, et al.*2023 · 6 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-learning-learn-test-time/)
14. **[SWE-chat: Coding Agent Interactions From Real Users in the Wild ↗](https://arxiv.org/abs/2604.20779) arXiv (Cornell University) · no summary yet**Joachim Baumann et al.*2026 · 5 citations*
15. **[SpecEval: Evaluating Model Adherence to Behavior Specifications ↗](https://arxiv.org/abs/2509.02464) arXiv (Cornell University) · no summary yet**Ahmed Abdelmoamen Ahmed et al.*2025 · 3 citations*
16. **[Language Models May Verbatim Complete Text They Were Not Explicitly Trained On ↗](https://arxiv.org/abs/2503.17514) arXiv (Cornell University) · no summary yet**Ken Ziyu Liu et al.*2025 · 3 citations*
17. **[Reliable and Efficient Amortized Model-based Evaluation ↗](https://arxiv.org/abs/2503.13335) arXiv (Cornell University) · no summary yet**Sang Truong et al.*2025 · 3 citations*
18. **[Shaping AI's Impact on Billions of Lives ↗](https://arxiv.org/abs/2412.02730) arXiv (Cornell University) · no summary yet**Mariano-Florentino Cuéllar et al.*2024 · 2 citations*
19. **[Inference-Time Control for Trustworthy Large Language Models ↗](https://doi.org/10.20944/preprints202605.1041.v1) Preprints.org · no summary yet**Yuyang Bai et al.*2026*
20. **[DecodingTrust-Agent Platform (DTap): A Controllable and Interactive Red-Teaming Platform for AI Agents ↗](https://arxiv.org/abs/2605.04808) arXiv (Cornell University) · no summary yet**Zhaorun Chen et al.*2026*
21. **[Verbalizing Subliminal Learning Effects Using Text Optimization ↗](https://arxiv.org/abs/2609.16927) arXiv (Cornell University) · no summary yet**Nathan Hu, Sanmi Koyejo, Christopher E. Potts*2026*
22. **[Verifiable, Articulable, and Tacit Components of Preference ↗](https://arxiv.org/abs/2610.03025) arXiv (Cornell University) · no summary yet**Alexander Spangher et al.*2026*
23. **[Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settings ↗](https://arxiv.org/abs/2601.06505) arXiv (Cornell University) · no summary yet**Sang Truong et al.*2026*
24. **[The Illusion of Robustness: Aggregate Accuracy Hides Prediction Flips under Task-Irrelevant Context ↗](https://arxiv.org/abs/2607.12963) arXiv (Cornell University) · no summary yet**Yanzhe Zhang, Sanmi Koyejo, Diyi Yang*2026*
25. **[Structured Prompts Improve Evaluation of Language Models ↗](https://arxiv.org/abs/2511.20836) arXiv (Cornell University) · no summary yet**Asad Aali et al.*2025*
26. **[Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF ↗](https://arxiv.org/abs/2503.22137) arXiv (Cornell University) · no summary yet**Syrine Belakaria et al.*2025*
27. **[Spatiotemporal generative AI for multimodal and multiscale modeling of geospatial data ↗](https://doi.org/10.25740/rp813np6409) Stanford Digital Repository · no summary yet**Jeremy Irvin et al.*2025*