Maxim Panov

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

2017–2026

Best venue rank

Where they publish

Papers

43 indexed papers, newest first.

Year	Venue	Title	Authors
2026	ACL	Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval-Augmented Generation.	Ekaterina Fadeeva, Aleksandr Rubashevskii, Dzianis Piatrashyn, Roman Vashurin, Shehzaad Dhuliawala, Artem Shelmanov, Timothy Baldwin, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
2026	ECIR	Uncertainty Quantification for Large Language Models.	Maxim Panov, Artem Shelmanov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Lyudmila Rvanova, Timothy Baldwin
2025	ACL	Uncertainty Quantification for Large Language Models.	Artem Shelmanov, Maxim Panov, Roman Vashurin, Artem Vazhentsev, Ekaterina Fadeeva, Timothy Baldwin
2025	EMNLP	UNCERTAINTY-LINE: Length-Invariant Estimation of Uncertainty for Large Language Models.	Roman Vashurin, Maiya Goloburda, Preslav Nakov, Maxim Panov
2025	EMNLP	Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models.	Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, Gleb Kuzmin, Ivan Lazichny, Alexander Panchenko, Preslav Nakov, Timothy Baldwin, Maxim Panov, Artem Shelmanov
2025	ICLR	From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation.	Nikita Kotelevskii, Vladimir Kondratyev, Martin Takc, Eric Moulines, Maxim Panov
2025	ICLR	Probabilistic Conformal Prediction with Approximate Conditional Validity.	Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines
2025	ICML	Rectifying Conformity Scores for Better Conditional Coverage.	Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
2025	NAACL	Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models.	Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2025	SDM	Learning Confident Classifiers in the Presence of Label Noise.	Asma Ahmed Hashmi, Aigerim Zhumabayeva, Nikita Kotelevskii, Artem Agafonov, Mohammad Yaqub, Maxim Panov, Martin Takc
2024	ACL	Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification.	Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov
2024	AIST	Automatic Adaptive Conformal Inference for Time Series Forecasting.	Artem Makhin, Maxim Panov
2024	AISTATS	Efficient Conformal Prediction under Data Heterogeneity.	Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horvth, Martin Takc, Eric Moulines, Maxim Panov
2024	EMNLP	Reference-free Hallucination Detection for Large Vision-Language Models.	Qing Li, Jiahui Geng, Chenyang Lyu, Derui Zhu, Maxim Panov, Fakhri Karray
2024	ICLR	Generalization error of spectral algorithms.	Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
2024	IJCAI	Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks.	Nikita Kotelevskii, Samuel Horvth, Karthik Nandakumar, Martin Takc, Maxim Panov
2023	ACL	Hybrid Uncertainty Quantification for Selective Text Classification in Ambiguous Tasks.	Artem Vazhentsev, Gleb Kuzmin, Akim Tsvigun, Alexander Panchenko, Maxim Panov, Mikhail Burtsev, Artem Shelmanov
2023	ACL	Efficient Out-of-Domain Detection for Sequence to Sequence Models.	Artem Vazhentsev, Akim Tsvigun, Roman Vashurin, Sergey Petrakov, Daniil Vasilev, Maxim Panov, Alexander Panchenko, Artem Shelmanov
2023	ACML	Selective Nonparametric Regression via Testing.	Fedor Noskov, Alexander Fishkov, Maxim Panov
2023	AIST	Distributed Bayesian Coresets.	Vladimir Omelyusik, Maxim Panov
2023	DSAA	ScaleFace: Uncertainty-aware Deep Metric Learning.	Roman Kail, Kirill Fedyanin, Nikita Muravev, Alexey Zaytsev, Maxim Panov
2023	EMNLP	LM-Polygraph: Uncertainty Estimation for Language Models.	Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, Artem Shelmanov
2023	ICCS	Real-Time Reconstruction of Complex Flow in Nanoporous Media: Linear vs Non-linear Decoding.	Emmanuel Akeweje, Andrey Olhin, Vsevolod Avilkin, Aleksey Vishnyakov, Maxim Panov
2023	ICML	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift.	Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	IJCNLP	Uncertainty Estimation for Debiased Models: Does Fairness Hurt Reliability?	Gleb Kuzmin, Artem Vazhentsev, Artem Shelmanov, Xudong Han, Simon Suster, Maxim Panov, Alexander Panchenko, Timothy Baldwin
2023	UAI	Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective.	Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Guillaud
2023	SDM	Scalable Batch Acquisition for Deep Bayesian Active Learning.	Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
2022	ACL	Uncertainty Estimation of Transformer Predictions for Misclassification Detection.	Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, Manvel Avetisian, Leonid Zhukov
2022	AISTATS	Embedded Ensembles: infinite width limit and operating regimes.	Maksim Velikanov, Roman V. Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky
2022	EMNLP	Active Learning for Abstractive Text Summarization.	Akim Tsvigun, Ivan Lysenko, Danila Sedashov, Ivan Lazichny, Eldar Damirov, Vladimir Karlov, Artemy Belousov, Leonid Sanochkin, Maxim Panov, Alexander Panchenko, Mikhail Burtsev, Artem Shelmanov
2021	AIST	Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling.	Kirill Fedyanin, Evgenii Tsymbalov, Maxim Panov
2021	AIST	Scalable Computation of Prediction Intervals for Neural Networks via Matrix Sketching.	Alexander Fishkov, Maxim Panov
2021	EACL	How Certain is Your Transformer?	Artem Shelmanov, Evgenii Tsymbalov, Dmitry Puzyrev, Kirill Fedyanin, Alexander Panchenko, Maxim Panov
2021	ICML	Monte Carlo Variational Auto-Encoders.	Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
2020	DSAA	Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data: Extended Abstract.	Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov
2020	ICDM	EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data.	Ivan Sukharev, Valentina Shumovskaia, Kirill Fedyanin, Maxim Panov, Dmitry Berestnev
2020	WWW	NCVis: Noise Contrastive Approach for Scalable Visualization.	Aleksandr Artemenkov, Maxim Panov
2019	ACML	Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension.	Marina Gomtsyan, Nikita Mokrov, Maxim Panov, Yury Yanovich
2019	IJCAI	Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning.	Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov
2019	IECON	Data-Driven Body-Machine Interface for Drone Intuitive Control through Voice and Gestures.	Alexander Menshchikov, Dmitry Ermilov, I. Dranitsky, L. Kupchenko, Maxim Panov, Maxim V. Fedorov, Andrey Somov
2018	AIST	Dropout-Based Active Learning for Regression.	Evgenii Tsymbalov, Maxim Panov, Alexander Shapeev
2018	ICDM	Constructing Graph Node Embeddings via Discrimination of Similarity Distributions.	Maxim Panov, Stanislav Tsepa
2017	ICMLA	Automatic Bitcoin Address Clustering.	Dmitry Ermilov, Maxim Panov, Yury Yanovich