Nikolay Malkin

98 papers A* 24A 4C 1Journal 63Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces. CoRR Arran Carter, Sanghyeok Choi, Kirill Tamogashev, Víctor Elvira, Nikolay Malkin
2026	J	`jnl`	From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training. Trans. Mach. Learn. Res. Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin
2026	J	`jnl`	Likelihood hacking in probabilistic program synthesis. CoRR Jacek Karwowski, Younesse Kaddar, Zihuiwen Ye, Nikolay Malkin, Sam Staton
2025	J	`jnl`	A Comedy of Estimators: On KL Regularization in RL Training of LLMs. CoRR Vedant Shah, Johan S. Obando-Ceron, Vineet Jain, Brian R. Bartoldson, Bhavya Kailkhura, Sarthak Mittal, Glen Berseth, Pablo Samuel Castro, Yoshua Bengio, Nikolay Malkin, Moksh Jain, Siddarth Venkatraman, Aaron C. Courville
2025	A*	`conf`	Action abstractions for amortized sampling. ICLR Oussama Boussif, Léna Néhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio
2025	J	`jnl`	Adaptive Destruction Processes for Diffusion Samplers. CoRR Timofei Gritsaev, Nikita Morozov, Kirill Tamogashev, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry P. Vetrov, Nikolay Malkin
2025	A*	`conf`	Adaptive teachers for amortized samplers. ICLR Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio
2025	A	`conf`	Can a Bayesian Oracle Prevent Harm from an Agent? UAI Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar
2025	J	`jnl`	Data-to-Energy Stochastic Dynamics. CoRR Kirill Tamogashev, Nikolay Malkin
2025	J	`jnl`	Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings. CoRR Andreas Sochopoulos, Nikolay Malkin, Nikolaos Tsagkas, João Moura, Michael Gienger, Sethu Vijayakumar
2025	J	`jnl`	Forgetting is Everywhere. CoRR Ben Sanati, Thomas L. Lee, Trevor McInroe, Aidan Scannell, Nikolay Malkin, David Abel, Amos Storkey
2025	J	`jnl`	From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training. CoRR Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin
2025	J	`jnl`	In-Context Parametric Inference: Point or Distribution Estimators? CoRR Sarthak Mittal, Yoshua Bengio, Nikolay Malkin, Guillaume Lajoie
2025	J	`jnl`	Learning Decision Trees as Amortized Structure Inference. CoRR Mohammed Mahfoud, Ghait Boukachab, Michal Koziarski, Alex Hernández-García, Stefan Bauer, Yoshua Bengio, Nikolay Malkin
2025	A*	`conf`	Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. ICLR Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
2025	J	`jnl`	Lightweight Latent Reasoning for Narrative Tasks. CoRR Alexander Gurung, Nikolay Malkin, Mirella Lapata
2025	—	`conf`	Mixtures of In-Context Learners. ACL (1) Giwon Hong, Emile van Krieken, Edoardo Maria Ponti, Nikolay Malkin, Pasquale Minervini
2025	J	`jnl`	Multi-Marginal Flow Matching with Adversarially Learnt Interpolants. CoRR Oskar Kviman, Kirill Tamogashev, Nicola Branchini, Víctor Elvira, Jens Lagergren, Nikolay Malkin
2025	J	`jnl`	On Designing Diffusion Autoencoders for Efficient Generation and Representation Learning. CoRR Magdalena Proszewska, Nikolay Malkin, N. Siddharth
2025	A*	`conf`	Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models. ICML Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2025	J	`jnl`	Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models. CoRR Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2025	A*	`conf`	PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. ICLR Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin, Salma Salhi, Connor Stone, Laurence Perreault Levasseur, Yashar Hezaveh
2025	J	`jnl`	Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models. CoRR Siddarth Venkatraman, Vineet Jain, Sarthak Mittal, Vedant Shah, Johan S. Obando-Ceron, Yoshua Bengio, Brian R. Bartoldson, Bhavya Kailkhura, Guillaume Lajoie, Glen Berseth, Nikolay Malkin, Moksh Jain
2025	J	`jnl`	Reinforced sequential Monte Carlo for amortised sampling. CoRR Sanghyeok Choi, Sarthak Mittal, Víctor Elvira, Jinkyoo Park, Nikolay Malkin
2025	J	`jnl`	Robust Reinforcement Learning for Discrete Compositional Generation via General Soft Operators. CoRR Marco Jiralerspong, Esther Derman, Danilo Vucetic, Nikolay Malkin, Bilun Sun, Tianyu Zhang, Pierre-Luc Bacon, Gauthier Gidel
2025	J	`jnl`	Solving Bayesian inverse problems with diffusion priors and off-policy RL. CoRR Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yashar Hezaveh, Laurence Perreault Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2024	J	`jnl`	Action abstractions for amortized sampling. CoRR Oussama Boussif, Léna Néhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio
2024	J	`jnl`	Adaptive teachers for amortized samplers. CoRR Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio
2024	A*	`conf`	Amortizing intractable inference in diffusion models for vision, language, and control. NeurIPS Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2024	J	`jnl`	Amortizing intractable inference in diffusion models for vision, language, and control. CoRR Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2024	A*	`conf`	Amortizing intractable inference in large language models. ICLR Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
2024	J	`jnl`	Can a Bayesian Oracle Prevent Harm from an Agent? CoRR Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar
2024	A*	`conf`	Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
2024	A	`conf`	Discrete Probabilistic Inference as Control in Multi-path Environments. UAI Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
2024	J	`jnl`	Discrete Probabilistic Inference as Control in Multi-path Environments. CoRR Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
2024	A*	`conf`	Expected flow networks in stochastic environments and two-player zero-sum games. ICLR Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
2024	A*	`conf`	Improved off-policy training of diffusion samplers. NeurIPS Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
2024	A*	`conf`	Improving Gradient-Guided Nested Sampling for Posterior Inference. ICML Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
2024	J	`jnl`	Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio
2024	A*	`conf`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
2024	J	`jnl`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
2024	J	`jnl`	Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
2024	J	`jnl`	Machine learning and information theory concepts towards an AI Mathematician. CoRR Yoshua Bengio, Nikolay Malkin
2024	J	`jnl`	Mixtures of In-Context Learners. CoRR Giwon Hong, Emile van Krieken, Edoardo M. Ponti, Nikolay Malkin, Pasquale Minervini
2024	J	`jnl`	On Generalization for Generative Flow Networks. CoRR Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio
2024	J	`jnl`	On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. CoRR Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
2024	J	`jnl`	PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. CoRR Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh
2024	A*	`conf`	PhyloGFN: Phylogenetic inference with generative flow networks. ICLR Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
2024	J	`jnl`	Proof Flow: Preliminary Study on Generative Flow Network Language Model Tuning for Formal Reasoning. CoRR Matthew Ho, Vincent Zhu, Xiaoyin Chen, Moksh Jain, Nikolay Malkin, Edwin Zhang
2024	A	`conf`	Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
2024	J	`jnl`	V-STaR: Training Verifiers for Self-Taught Reasoners. CoRR Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron C. Courville, Alessandro Sordoni, Rishabh Agarwal
2023	A*	`conf`	A theory of continuous generative flow networks. ICML Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
2023	J	`jnl`	A theory of continuous generative flow networks. CoRR Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
2023	J	`jnl`	Amortizing intractable inference in large language models. CoRR Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
2023	J	`jnl`	BatchGFN: Generative Flow Networks for Batch Active Learning. CoRR Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal
2023	A*	`conf`	Better Training of GFlowNets with Local Credit and Incomplete Trajectories. ICML Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
2023	J	`jnl`	Better Training of GFlowNets with Local Credit and Incomplete Trajectories. CoRR Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
2023	J	`jnl`	Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio
2023	J	`jnl`	Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
2023	J	`jnl`	Discrete, compositional, and symbolic representations through attractor dynamics. CoRR Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie
2023	J	`jnl`	Expected flow networks in stochastic environments and two-player zero-sum games. CoRR Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
2023	A*	`conf`	GFlowNet-EM for Learning Compositional Latent Variable Models. ICML Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie E. Everett, Alexandros Graikos, Yoshua Bengio
2023	J	`jnl`	GFlowNet-EM for learning compositional latent variable models. CoRR Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio
2023	A*	`conf`	GFlowNets and variational inference. ICLR Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
2023	A*	`conf`	GFlowOut: Dropout with Generative Flow Networks. ICML Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
2023	J	`jnl`	Improving Gradient-guided Nested Sampling for Posterior Inference. CoRR Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
2023	A*	`conf`	Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. NeurIPS Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
2023	J	`jnl`	Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. CoRR Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
2023	A*	`conf`	Learning GFlowNets From Partial Episodes For Improved Convergence And Stability. ICML Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
2023	J	`jnl`	Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	A*	`conf`	Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	J	`jnl`	PhyloGFN: Phylogenetic inference with generative flow networks. CoRR Mingyang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
2023	J	`jnl`	Simulation-free Schrödinger bridges via score and flow matching. CoRR Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
2023	—	`conf`	ThinkSum: Probabilistic reasoning over sets using large language models. ACL (1) Batu Ozturkler, Nikolay Malkin, Zhen Wang, Nebojsa Jojic
2023	J	`jnl`	Thompson sampling for improved exploration in GFlowNets. CoRR Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio
2022	—	`conf`	Coherence boosting: When your pretrained language model is not paying enough attention. ACL (1) Nikolay Malkin, Zhen Wang, Nebojsa Jojic
2022	A*	`conf`	Diffusion Models as Plug-and-Play Priors. NeurIPS Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
2022	J	`jnl`	Diffusion models as plug-and-play priors. CoRR Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
2022	J	`jnl`	GFlowNets and variational inference. CoRR Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
2022	J	`jnl`	GFlowOut: Dropout with Generative Flow Networks. CoRR Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
2022	A*	`conf`	Generative Flow Networks for Discrete Probabilistic Modeling. ICML Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
2022	J	`jnl`	Generative Flow Networks for Discrete Probabilistic Modeling. CoRR Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
2022	J	`jnl`	Learning GFlowNets from partial episodes for improved convergence and stability. CoRR Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
2022	J	`jnl`	Posterior samples of source galaxies in strong gravitational lenses with score-based priors. CoRR Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio
2022	A	`conf`	Resolving label uncertainty with implicit posterior models. UAI Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic
2022	J	`jnl`	Resolving label uncertainty with implicit posterior models. CoRR Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic
2022	J	`jnl`	The Outcome of the 2021 IEEE GRSS Data Fusion Contest - Track MSD: Multitemporal Semantic Change Detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Zhuohong Li, Fangxiao Lu, Hongyan Zhang, Lilin Tu, Jiayi Li, Xin Huang, Caleb Robinson, Nikolay Malkin, Nebojsa Jojic, Pedram Ghamisi, Ronny Hänsch, Naoto Yokoya
2022	J	`jnl`	ThinkSum: Probabilistic reasoning over sets using large language models. CoRR Batu Ozturkler, Nikolay Malkin, Zhen Wang, Nebojsa Jojic
2022	J	`jnl`	Trajectory Balance: Improved Credit Assignment in GFlowNets. CoRR Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
2022	A*	`conf`	Trajectory balance: Improved credit assignment in GFlowNets. NeurIPS Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
2022	J	`jnl`	Unifying Generative Models with GFlowNets. CoRR Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, Yoshua Bengio
2021	J	`jnl`	Boosting coherence of language models. CoRR Nikolay Malkin, Zhen Wang, Nebojsa Jojic
2021	C	`conf`	From Local Algorithms to Global Results: Human-Machine Collaboration for Robust Analysis of Geographically Diverse Imagery. IGARSS Nebojsa Jojic, Nikolay Malkin, Caleb Robinson, Anthony Ortiz
2021	—	`conf`	GPT Perdetry Test: Generating new meanings for new words. NAACL-HLT Nikolay Malkin, Sameera Lanka, Pranav Goel, Sudha Rao, Nebojsa Jojic
2021	J	`jnl`	High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest. CoRR Nikolay Malkin, Caleb Robinson, Nebojsa Jojic
2021	—	`conf`	Studying word order through iterative shuffling. EMNLP (1) Nikolay Malkin, Sameera Lanka, Pranav Goel, Nebojsa Jojic
2021	J	`jnl`	Studying word order through iterative shuffling. CoRR Nikolay Malkin, Sameera Lanka, Pranav Goel, Nebojsa Jojic
2020	—	`conf`	Mining Self-similarity: Label Super-Resolution with Epitomic Representations. ECCV (26) Nikolay Malkin, Anthony Ortiz, Nebojsa Jojic