Moksh Jain - RankMe

51 papers A* 14A 1Journal 35Unranked 1

Year	Rank	Type	Title / Venue / Authors
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`	Benchmarking World-Model Learning. CoRR Archana Warrier, Dat Nguyen, Michelangelo Naim, Moksh Jain, Yichao Liang, Karen Schroeder, Cambridge Yang, Joshua B. Tenenbaum, Sebastian J. Vollmer, Kevin Ellis, Zenna Tavares
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`	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`	Search-Based Correction of Reasoning Chains for Language Models. CoRR Minsu Kim, Jean-Pierre R. Falet, Oliver E. Richardson, Xiaoyin Chen, Moksh Jain, Sungjin Ahn, Sungsoo Ahn, Yoshua Bengio
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
2025	J	`jnl`	Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. CoRR Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
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	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`	Automated Discovery of Pairwise Interactions from Unstructured Data. CoRR Zuheng Xu, Moksh Jain, Ali Denton, Shawn Whitfield, Aniket Didolkar, Berton Earnshaw, Jason S. Hartford
2024	J	`jnl`	Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio
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`	Multi-Fidelity Active Learning with GFlowNets. Trans. Mach. Learn. Res. Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio
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	A*	`conf`	Pre-Training and Fine-Tuning Generative Flow Networks. ICLR Ling Pan, Moksh Jain, Kanika Madan, 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	J	`jnl`	Towards DNA-Encoded Library Generation with GFlowNets. CoRR Michal Koziarski, Mohammed Abukalam, Vedant Shah, Louis Vaillancourt, Doris Alexandra Schuetz, Moksh Jain, Almer van der Sloot, Mathieu Bourgey, Anne Marinier, Yoshua Bengio
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	J	`jnl`	DEUP: Direct Epistemic Uncertainty Prediction. Trans. Mach. Learn. Res. Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
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	J	`jnl`	GFlowNets for AI-Driven Scientific Discovery. CoRR Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, 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	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`	Multi-Fidelity Active Learning with GFlowNets. CoRR Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio
2023	A*	`conf`	Multi-Objective GFlowNets. ICML Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
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`	Pre-Training and Fine-Tuning Generative Flow Networks. CoRR Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio
2023	A	`conf`	Stochastic Generative Flow Networks. UAI Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio
2023	J	`jnl`	Stochastic Generative Flow Networks. CoRR Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio
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	A*	`conf`	Biological Sequence Design with GFlowNets. ICML Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
2022	J	`jnl`	Biological Sequence Design with GFlowNets. CoRR Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
2022	J	`jnl`	Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. CoRR Chanakya Ekbote, Moksh Jain, Payel Das, 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	J	`jnl`	Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. CoRR Bonaventure F. P. Dossou, Dianbo Liu, Xu Ji, Moksh Jain, Almer M. van der Sloot, Roger Palou, Michael Tyers, 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`	Multi-Objective GFlowNets. CoRR Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
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
2021	J	`jnl`	DEUP: Direct Epistemic Uncertainty Prediction. CoRR Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
2021	A*	`conf`	Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. NeurIPS Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
2021	J	`jnl`	Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. CoRR Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
2020	A*	`conf`	DROCC: Deep Robust One-Class Classification. ICML Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
2020	J	`jnl`	DROCC: Deep Robust One-Class Classification. CoRR Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
2020	—	`conf`	Improving Convergence in IRGAN with PPO. COMAD/CODS Moksh Jain, S. Sowmya Kamath
2019	J	`jnl`	Proximal Policy Optimization for Improved Convergence in IRGAN. CoRR Moksh Jain, Sowmya Kamath S.