--- title: "Aditya Grover — author profile and papers — Elamur Research" description: "Aditya Grover, University of California, Los Angeles: 2 papers on Elamur Research (2025–2026), h-index 24 — affiliations, topics, co-authors…" canonical: "https://research.elamur.ai/free/en/authors/aditya-grover/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/aditya-grover/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Aditya Grover # Aditya Grover Aditya Grover has 2 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Anna Rohrbach](https://md.research.elamur.ai/free/en/authors/anna-rohrbach/), [Arian Hosseini](https://md.research.elamur.ai/free/en/authors/arian-hosseini/), [Hritik Bansal](https://md.research.elamur.ai/free/en/authors/hritik-bansal/). 2 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5014409944) · [ORCID](https://orcid.org/0000-0002-4217-6624) · [**h-index 24**](https://openalex.org/authors/A5014409944) · [116 works](https://openalex.org/works?filter=author.id:A5014409944) · [14,463 citations](https://openalex.org/works?filter=author.id:A5014409944&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/aditya-grover/#papers) · [🔗 Cited 663 times in our library](https://md.research.elamur.ai/free/en/authors/aditya-grover/cited-by/) · [25 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #7750](https://md.research.elamur.ai/free/en/paper-stars/page/78/#star-7750) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Aditya+Grover) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Aditya+Grover) · [dblp](https://dblp.org/search?q=Aditya+Grover) · [ACL Anthology](https://aclanthology.org/search/?q=Aditya+Grover) ## Affiliations [🎓**University of California, Los Angeles** Los Angeles · United States 2020–2026 · 45 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-los-angeles/) · [🎓**Stanford University** Stanford · United States 2016–2021 · 27 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🏢**Meta** Menlo Park · United States 2020–2022 · 6 papers](https://md.research.elamur.ai/free/en/companies/meta/) · [🎓**University of California, Berkeley** Berkeley · United States 2020–2022 · 4 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) · [🎓**Indian Institute of Technology Delhi** New Delhi · India 2015–2016 · 4 papers](https://md.research.elamur.ai/free/en/universities/indian-institute-of-technology-delhi/) 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. 📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) 💡 Concepts 1 Key ideas and methods explained on our concept pages.[Scaling laws · 1 work](https://md.research.elamur.ai/free/en/concepts/scaling-laws/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/aditya-grover/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/aditya-grover/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)** *(2026 · 97 citations)* Reasoning-oriented post-training of LLMs usually relies on RLVR (e.g., GRPO), SFT, or distillation from a stronger teacher, and each has a weakness. 2. **[When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)** *(2025 · 12 citations)* Large language models can spend extra test-time compute on reasoning in two main ways. The first is Self-Consistency (SC), which samples many candidate solutions and takes a majority vote. The second samples fewer solutions and ranks them with a Generative Reward Model (GenRM), which writes several verification… ## All works 27 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. **[node2vec ↗](https://doi.org/10.1145/2939672.2939754) ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yet**Aditya Grover, Jure Leskovec*2016 · 10,750 citations* 2. **[Closed-loop optimization of fast-charging protocols for batteries with machine learning ↗](https://doi.org/10.1038/s41586-020-1994-5) Nature · no summary yet**Peter M. Attia et al.*2020 · 1,155 citations* 3. **[node2vec: Scalable Feature Learning for Networks ↗](https://arxiv.org/abs/1607.00653) PubMed · no summary yet**Aditya Grover, Jure Leskovec*2016 · 484 citations* 4. **[Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models ↗](https://doi.org/10.1609/aaai.v32i1.11829) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Aditya Grover, Manik Dhar, Stefano Ermon*2018 · 204 citations* 5. **[Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols ↗](https://doi.org/10.1016/j.joule.2021.10.010) Joule · no summary yet**Benben Jiang et al.*2021 · 128 citations* 6. **[Frozen Pretrained Transformers as Universal Computation Engines ↗](https://doi.org/10.1609/aaai.v36i7.20729) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Kevin Lu et al.*2022 · 123 citations* 7. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/) 8. **[Stochastic Optimization of Sorting Networks via Continuous Relaxations ↗](https://arxiv.org/abs/1903.08850) arXiv (Cornell University) · no summary yet**Aditya Grover et al.*2019 · 89 citations* 9. **[Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting ↗](https://arxiv.org/abs/1906.09531) arXiv (Cornell University) · no summary yet**Aditya Grover et al.*2019 · 80 citations* 10. **[Learning Controllable Fair Representations ↗](https://arxiv.org/abs/1812.04218) arXiv (Cornell University) · no summary yet**Jiaming Song et al.*2018 · 70 citations* 11. **[Graphite: Iterative Generative Modeling of Graphs ↗](https://arxiv.org/abs/1803.10459) arXiv (Cornell University) · no summary yet**Aditya Grover, Aaron Zweig, Stefano Ermon*2018 · 48 citations* 12. **[Modeling Sparse Deviations for Compressed Sensing using Generative Models ↗](https://arxiv.org/abs/1807.01442) arXiv (Cornell University) · no summary yet**Manik Dhar, Aditya Grover, Stefano Ermon*2018 · 43 citations* 13. **[Boosted Generative Models ↗](https://doi.org/10.1609/aaai.v32i1.11827) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Aditya Grover, Stefano Ermon*2018 · 42 citations* 14. **[Mercury: Ultra-Fast Language Models Based on Diffusion ↗](https://arxiv.org/abs/2506.17298) arXiv:2506.17298 · no summary yet**Inception Labs et al.*2025 · 36 citations* 15. **[Permutation Invariant Graph Generation via Score-Based Generative Modeling ↗](https://arxiv.org/abs/2003.00638) arXiv (Cornell University) · no summary yet**Chenhao Niu et al.*2020 · 34 citations* 16. **[Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization ↗](https://arxiv.org/abs/1812.10539) arXiv (Cornell University) · no summary yet**Aditya Grover, Stefano Ermon*2018 · 31 citations* 17. **[Best arm identification in multi-armed bandits with delayed feedback ↗](https://arxiv.org/abs/1803.10937) arXiv (Cornell University) · no summary yet**Aditya Grover et al.*2018 · 27 citations* 18. **[Fair Generative Modeling via Weak Supervision ↗](https://arxiv.org/abs/1910.12008) arXiv (Cornell University) · no summary yet**Kristy Choi et al.*2019 · 15 citations* 19. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/) 20. **[PiRank: Scalable Learning To Rank via Differentiable Sorting ↗](https://arxiv.org/abs/2012.06731) arXiv (Cornell University) · no summary yet**Robin M. E. Swezey et al.*2020 · 9 citations* 21. **[Anytime Sampling for Autoregressive Models via Ordered Autoencoding ↗](https://arxiv.org/abs/2102.11495) arXiv (Cornell University) · no summary yet**Yilun Xu et al.*2021 · 8 citations* 22. **[Streamlining variational inference for constraint satisfaction problems* ↗](https://doi.org/10.1088/1742-5468/ab371f) Journal of Statistical Mechanics Theory and Experiment · no summary yet**Aditya Grover, Tudor Achim, Stefano Ermon*2019 · 6 citations* 23. **[Variational Rejection Sampling ↗](https://arxiv.org/abs/1804.01712) arXiv (Cornell University) · no summary yet**Aditya Grover et al.*2018 · 6 citations* 24. **[BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery ↗](https://arxiv.org/abs/2112.02761) arXiv (Cornell University) · no summary yet**Chris Cundy, Aditya Grover, Stefano Ermon*2021 · 4 citations* 25. **[Variational Bayes on Monte Carlo Steroids ↗](https://openalex.org/W2554637102) neural information processing systems · no summary yet**Aditya Grover, Stefano Ermon*2016 · 4 citations* [See all 27 works by Aditya Grover →](https://md.research.elamur.ai/free/en/authors/aditya-grover/works/) ## Co-authors here 7 co-authors with a page, the most papers together first. - [Anna Rohrbach](https://md.research.elamur.ai/free/en/authors/anna-rohrbach/) - [Arian Hosseini](https://md.research.elamur.ai/free/en/authors/arian-hosseini/) - [Hritik Bansal](https://md.research.elamur.ai/free/en/authors/hritik-bansal/) - [Jing Huang](https://md.research.elamur.ai/free/en/authors/jing-huang/) - [Kai-Wei Chang](https://md.research.elamur.ai/free/en/authors/kai-wei-chang/) - [Marcus Rohrbach](https://md.research.elamur.ai/free/en/authors/marcus-rohrbach/) - [Zhihui Xie](https://md.research.elamur.ai/free/en/authors/zhihui-xie/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Proceedings of the AAAI Conference on Artificial Intelligence ×3 - ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) - International Conference on Learning Representations - Joule - Journal of Statistical Mechanics Theory and Experiment - Nature - PubMed - neural information processing systems ## Cited by Papers of our library cite their works 663 times (of the 149,439 papers whose bibliographies we read); [63 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/aditya-grover/cited-by/). Updated 2 November 2026