2025 2025 Under Rev. HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs Azim Ospanov, Zijin Feng, Jiacheng Sun, and 3 more authors Nov 2025 PDF NeurIPS APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning Azim Ospanov, Farzan Farnia, and Roozbeh Yousefzadeh In The Thirty-ninth Annual Conference on Neural Information Processing Systems, Nov 2025 PDF NeurIPS miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path Forward Azim Ospanov, Farzan Farnia, and Roozbeh Yousefzadeh In The Thirty-ninth Annual Conference on Neural Information Processing Systems, Nov 2025 PDF ICCV Scendi Score: Prompt-Aware Diversity Evaluation via Schur Complement of CLIP Embeddings Azim Ospanov, Mohammad Jalali, and Farzan Farnia In International Conference on Computer Vision, Oct 2025 PDF UAI Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees Azim Ospanov and Farzan Farnia In The 41st Conference on Uncertainty in Artificial Intelligence, Jul 2025 PDF TMLR A Lean Dataset for International Math Olympiad: Small Steps towards Writing Math Proofs for Hard Problems Roozbeh Yousefzadeh, Xuenan Cao, and Azim Ospanov Transactions on Machine Learning Research, Feb 2025 PDF 2024 2024 NeurIPS Towards a Scalable Reference-Free Evaluation of Generative Models Azim Ospanov, Jingwei Zhang, Mohammad Jalali, and 3 more authors In The Thirty-eighth Annual Conference on Neural Information Processing Systems, Nov 2024 PDF Code Under Rev. Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative Models Mohammad Jalali, Azim Ospanov, Amin Gohari, and 1 more author Nov 2024 PDF
Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative ModelsNov 2024 