Du 10 au 15 décembre, les chercheuses et chercheurs de Mila participeront à la trente-huitième conférence annuelle sur les systèmes de traitement de l'information neuronale (NeurIPS 2024) à Vancouver, au Canada.
Cette année, elles et ils présenteront plus de 60 publications scientifiques lors de la conférence principale afin de partager les résultats de leur recherche en intelligence artificielle (IA) avec leurs pairs du monde entier. Elles et ils présenteront également des dizaines de publications lors d’ateliers thématiques.
Voici une liste des articles acceptés à NeurIPS 2024 qui contiennent au moins un·e auteur·rice affilié·e à Mila:
Conférence principale
| Title | Authors |
|---|---|
| Cell ontology guided transcriptome foundation model | Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang |
| Balancing Context Length and Mixing Times for Reinforcement Learning at Scale | Matthew D Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar |
| Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences | Damien Ferbach, Quentin Bertrand, Joey Bose, Gauthier Gidel |
| Normalization and effective learning rates in reinforcement learning | Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney |
| Amortizing intractable inference in diffusion models for vision, language, and control | Siddarth Venkatraman, Moksh J. 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 |
| Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving | Aniket Rajiv Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael Curtis Mozer, Sanjeev Arora |
| QGFN: Controllable Greediness with Action Values | Elaine Lau, Stephen Zhewen Lu, Ling Pan, Doina Precup, Emmanuel Bengio |
| Parseval Regularization for Continual Reinforcement Learning | Wesley Chung, Lynn Cherif, Doina Precup, David Meger |
| RGFN: Synthesizable Molecular Generation Using GFlowNets | Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer M. van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey |
| Listenable Maps for Zero-Shot Audio Classifiers | Francesco Paissan, Luca Della Libera, Mirco Ravanelli, Cem Subakan |
| A Generative Model of Symmetry Transformations | James Urquhart Allingham, Bruno Mlodozeniec, Shreyas Padhy, Javier Antoran, David Krueger, Richard E. Turner, Eric Nalisnick, José Miguel Hernández-Lobato |
| Adaptive Exploration for Data-Efficient General Value Function Evaluations | Arushi Jain, Josiah P. Hanna, Doina Precup |
| Efficient Leverage Score Sampling for Tensor Train Decomposition | Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau |
| Many-Shot In-Context Learning | Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle |
| A Foundation Model for Zero-shot Logical Query Reasoning | Mikhail Galkin, Jincheng Zhou, Bruno Ribeiro, Jian Tang, Zhaocheng Zhu |
| Efficient Reinforcement Learning by Discovering Neural Pathways | Samin Yeasar Arnob, Riyasat Ohib, Sergey Plis, Amy Zhang, Alessandro Sordoni, Doina Precup |
| How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval | Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini |
| Do LLMs Build World Representations? Probing Through the Lens of State Abstraction | Zichao Li, Yanshuai Cao, Jackie C. K. Cheung |
| ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation | Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini |
| Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn | Hongyao Tang, Glen Berseth |
| Code Repair with LLMs gives an Exploration-Exploitation Tradeoff | Hao Tang, Keya Hu, Jin Peng Zhou, Si Cheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis |
| Simplifying Constraint Inference with Inverse Reinforcement Learning | Adriana Hugessen, Harley Wiltzer, Glen Berseth |
| On the Scalability of GNNs for Molecular Graphs | Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini |
| The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More | Ouail Kitouni, Niklas Nolte, Adina Williams, Michael Rabbat, Diane Bouchacourt, Mark Ibrahim |
| Conformal Inverse Optimization | Bo Lin, Érick Delage, Timothy Chan |
| Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space | Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann |
| Offline Multitask Representation Learning for Reinforcement Learning | Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup |
| Improving Context-Aware Preference Modeling for Language Models | Silviu Pitis, Ziang Xiao, Nicolas Le Roux, Alessandro Sordoni |
| When is an Embedding Model More Promising than Another? | Maxime DARRIN, Philippe Formont, Ismail Ben Ayed, Jackie C. K. Cheung, Pablo Piantanida |
| Trajectory Flow Matching with Applications to Clinical Time Series Modelling | Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis Shung, Alexander Tong |
| Efficient Adversarial Training in LLMs with Continuous Attacks | Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn |
| HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation | Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates |
| Stress-Testing Capability Elicitation With Password-Locked Models | Ryan Greenblatt, Fabien Roger, Dmitrii Krasheninnikov, David Krueger |
| Geometry of naturalistic object representations in recurrent neural network models of working memory | Xiaoxuan Lei, Takuya Ito, Pouya Bashivan |
| Improved off-policy training of diffusion samplers | Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin |
| Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness | Ahmad Reza Ehyaei, Golnoosh Farnadi, Samira Samadi |
| Grounding Multimodal Large Language Models in Actions | Andrew Szot, Bogdan Mazoure, Harsh Agrawal, Devon Hjelm, Zsolt Kira, Alexander T Toshev |
| Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers | Jonas Ngnawe, Sabyasachi Sahoo, Yann Batiste Pequignot, Frederic Precioso, Christian Gagne |
| Harnessing small projectors and multiple views for efficient vision pretraining | Arna Ghosh, Kumar Krishna Agrawal, Shagun Sodhani, Adam Oberman, Blake Aaron Richards |
| Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval | Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, MARYAM KARIMZADEHGAN |
| Interpreting Learned Feedback Patterns in Large Language Models | Luke Marks, Amir Abdullah, Clement Neo, Rauno Arike, David Krueger, Philip Torr, Fazl Barez |
| Periodic agent-state based Q-learning for POMDPs | Amit Sinha, Matthieu Geist, Aditya Mahajan |
| On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models | Tariq Berrada, Pietro Astolfi, Melissa Hall, Reyhane Askari Hemmat, Yohann Benchetrit, Marton Havasi, Matthew J. Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal |
| VisMin: Visual Minimal-Change Understanding | Rabiul Awal, Saba Ahmadi, Le Zhang, Aishwarya Agrawal |
| 4+3 Phases of Compute-Optimal Neural Scaling Laws | Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington |
| On the Scalability of Certified Adversarial Robustness with Generated Data | Thomas Altstidl, David Dobre, Arthur Kosmala, Bjoern Eskofier, Gauthier Gidel, Leo Schwinn |
| Predicting Future Actions of Reinforcement Learning Agents | Stephen Chung, Scott Niekum, David Krueger |
| The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms | Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew Mackenzie, Elliot Paquette, Courtney Paquette |
| Multi-Scale Representation Learning for Protein Fitness Prediction | Zuobai Zhang, Pascal Notin, Yining Huang, Aurelie Lozano, Vijil Chenthamarakshan, Debora Susan Marks, Payel Das, Jian Tang |
| GenRL: Multimodal-foundation world models for generalization in embodied agents | Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron Courville, Sai Rajeswar |
| Towards a "Universal Translator" for Neural Dynamics at Single-Cell | Yizi Zhang, Yanchen Wang, Donato M. Jiménez-Benetó, Zixuan Wang, Mehdi Azabou, Blake Aaron Richards, Renee Tung, Olivier Winter, International Brain Laboratory, Eva L Dyer, Liam Paninski, Cole Lincoln Hurwitz |
| Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation | Guillaume Huguet, James Vuckovic, Kilian FATRAS, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Joey Bose |
| Metric Flow Matching for Smooth Interpolations on the Data Manifold | Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Joey Bose, Francesco Di Giovanni |
| Fisher Flow Matching for Generative Modelling over Discrete Data | Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkay Ceylan, Michael Bronstein, Joey Bose |
| Learning Action and Reasoning-Centric Image Editing from Videos and Simulation | Benno Krojer, Dheeraj Vattikonda, Luis Lara, Varun Jampani, Eva Portelance, Christopher Pal, Siva Reddy |
| Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning | Harley Wiltzer, Marc G. Bellemare, David Meger, Patrick Shafto, Yash Jhaveri |
| Foundations of Multivariate Distributional Reinforcement Learning | Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland |
| Learning Successor Features the Simple Way | Raymond Chua, Arna Ghosh, Christos Kaplanis, Blake Aaron Richards, Doina Precup |
| Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling | Yuanqi Du, Michael Plainer, Rob Brekelmans, Chenru Duan, Frank Noé, Carla P. Gomes, Alán Aspuru-Guzik, Kirill Neklyudov |
| MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions | Le Zhang, Jiayang Chen, Tao Shen, Yu Li, Siqi Sun |
| Slight Corruption in Pre-training Data Makes Better Diffusion Models | Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj |
| Towards training digitally-tied analog blocks via hybrid gradient computation | Nest, Timothy; Ernoult, Maxence |
| What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks | Yilun Zheng, Sitao Luan, Lihui Chen |
Dataset et Benchmark Track
| Title | Authors |
|---|---|
| Consent in Crisis: The Rapid Decline of the AI Data Commons | Shayne Longpre, Robert Mahari, Ariel Lee, Campbell Lund, Hamidah Oderinwale, William Brannon, Nayan Saxena, Naana Obeng-Marnu, Tobin South, Cole Hunter, Kevin Klyman, Christopher Klamm, Hailey Schoelkopf, Nikhil Singh, Manuel Cherep, Ahmad Anis, An Dinh, Caroline Chitongo, Da Yin, Damien Sileo, Deividas Mataciunas, Diganta Misra, Emad Alghamdi, Enrico Shippole, Jianguo Zhang, Joanna Materzynska, Kun Qian, Kush Tiwary, Lester Miranda, Manan Dey, Minnie Liang, Mohammed Hamdy, Niklas Muennighoff, Seonghyeon Ye, Seungone Kim, Shrestha Mohanty, Vipul Gupta, Vivek Sharma, Vu Minh Chien, Xuhui Zhou, Yizhi Li, Caiming Xiong, Luis Villa, Stella Biderman, Hanlin Li, Daphne Ippolito, Sara Hooker, Jad Kabbara, Sandy Pentland |
| WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks | Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin |
| RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content | Joao Monteiro, Pierre-Andre Noel, Étienne Marcotte, Sai Rajeswar, Valentina Zantedeschi, David Vazquez, Nicolas Chapados, Christopher Pal, Perouz Taslakian |
| Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection | Charles Guille-Escuret, Pierre-Andre Noel, Ioannis Mitliagkas, David Vazquez, Joao Monteiro |
| CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset | Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani, Aldo Zaimi, Ge Li, Nicolas Pouliot, Julien Beaudry, Gaetan Marceau Caron |
| Using Unity to Help Solve Reinforcement Learning | Connor Brennan, Andrew Robert Williams, Omar G. Younis, Vedant Vyas, Daria Yasafova, Irina Rish |
| CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark | David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo, Teresa Lynn, Injy Hamed, Aditya Nanda Kishore, Aishik Mandal, Alina Dragonetti, Artem Abzaliev, Atnafu Lambebo Tonja, Bontu Fufa Balcha, Chenxi Whitehouse, Christian Salamea, Dan John Velasco, David Ifeoluwa Adelani et al. |
| Reactzyme: A Benchmark for Enzyme-Reaction Prediction | Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng |
| CALE: Continuous Arcade Learning Environment | Jesse Farebrother, Pablo Samuel Castro |
Journal à Conference Track
| Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers | Fatemeh Nourilenjan Nokabadi, Jean-Francois Lalonde, Christian Gagné |
Creative AI Track
| Exploratory Study Of Human-AI Interaction For Hindustani Music | Nithya Shikarpur, Cheng-Zhi Anna Huang |
Ateliers
| Title | Authors |
| LO: Compute-Efficient Meta-Generalization of Learned Optimizers | Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky |
| General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data | Mohammad Javad Darvishi Bayazi, Hena Ghonia, Roland Riachi, Bruno Aristimunha, Arian Khorasani, Md Rifat Arefin, Amin Darabi, Guillaume Dumas, Irina Rish |
| Understanding Adam Requires Better Rotation Dependent Assumptions | Tianyue H. Zhang, Lucas Maes, Charles Guille-Escuret, Alexia Jolicoeur-Martineau, Ioannis Mitliagkas, Simon Lacoste-Julien, Damien Scieur |
| Crystal Design Amidst Noisy DFT Signals: A Reinforcement Learning Approach | Prashant Govindarajan, Mathieu Reymond, Santiago Miret, Mariano Phielipp, Sarath Chandar |
| HoneyComb: A Flexible LLM-Based Agent System for Materials Science | Huan Zhang, Yu Song, Ziyu Hou, Santiago Miret, Bang Liu |
| SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models | Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Qiang Zhu, Mikhail Galkin, Santiago Miret, Siamak Ravanbakhsh |
| MatExpert: Decomposing Materials Discovery By Mimicking Human Experts | Qianggang Ding, Santiago Miret, Bang Liu |
| Efficient Design-and-Control Automation with Reinforcement Learning and Adaptive Exploration | Jiajun Fan, Hongyao Tang, Michael Przystupa, Mariano Phielipp, Santiago Miret, Glen Berseth |
| LLMs and Personalities: Inconsistencies Across Scales | Tosato Tommaso, Mahmood Hegazy, David Lemay, Mohammed Abukalam, Irina Rish, Guillaume Dumas |
| Evaluating Interventional Reasoning Capabilities of Large Language Models | Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar |
| Testing causal hypotheses through Hierarchical Reinforcement Learning | Anthony GX-Chen, Dongyan Lin, Mandana Samiei |
| General Causal Imputation via Synthetic Interventions | Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel |
| Beyond Causal Discovery for Astronomy: Learning Meaningful Representations with Independent Component Analysis | Zehao Jin, Mario Pasquato, Benjamin L. Davis, A. Macciò, Yashar Hezaveh |
| MAP: Model Merging with Amortized Pareto Front Using Limited Computation | Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio |
| Learning Robust Representations for Transfer in Reinforcement Learning | Faisal Mohamed, Roger Creus Castanyer, Hongyao Tang, Zahra Sheikhbahaee, Glen Berseth |
| A Layer Selection Approach to Test Time Adaptation | Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawe, Yann Batiste Pequignot, Frederic Precioso, Christian Gagne |
| Faster, More Efficient RLHF through Off-Policy Asynchronous Learning | Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron Courville |
| Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval | Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini |
| Sample compression unleashed : New generalization bounds for real valued losses | Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain |
| On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy | Saber Malekmohammadi, Golnoosh Farnadi |
| Library Learning Doesn’t: The Curious Case of the Single-Use “Library” | Ian Berlot-Attwell, Frank Rudzicz, Xujie Si |
| AI-Assisted Generation of Difficult Math Questions | Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Jiatong Yu, Yinghui He, Nan Rosemary Ke, Michael Curtis Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal |
| VinePPO: Accurate Credit Assignment in RL for LLM Mathematical Reasoning | Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron Courville, Nicolas Le Roux |
| Fine-Tuning Web Agents: It Works, But It's Trickier Than You Think | Massimo Caccia, Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Nicolas Chapados, Alexandre Drouin, Maxime Gasse, Alexandre Lacoste |
| Hallucination Detox: Sensitive Neuron Dropout (SeND) for Large Language Model Training | Shahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, Golnoosh Farnadi |
| Unlearning in- vs. out-of-distribution data in LLMs under gradient-based methods | Teodora Baluta, Gintare Karolina Dziugaite, Pascal Lamblin, Fabian Pedregosa, Danny Tarlow |
| Identifying and Addressing Delusions for Target-Directed Decision-Making | Harry Zhao, Mingde Zhao, Tristan Sylvain, Doina Precup, Yoshua Bengio |
| Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity | David Williams-King, Linh Le, Adam Oberman, Yoshua Bengio |
| The Structural Safety Generalization Problem | Tom Gibbs, Julius Broomfield, George Ingebretsen, Ethan Kosak-Hine, Tia Nasir, Jason Zhang, Reihaneh Iranmanesh, Sara Pieri, Reihaneh Rabbany, Kellin Pelrine |
| Simulation System Towards Solving Societal-Scale Manipulation | Maximilian Puelma Touzel, Sneheel Sarangi, Austin Welch, Gayatri K, Dan Zhao, Zachary Yang, Hao Yu, Tom Gibbs, Ethan Kosak-Hine, Andreea Musulan, Camille Thibault, Busra Tugce Gurbuz, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine |
| Quantifying Likeness: A Simple Machine Learning Approach to Identifying Copyright Infringement in (AI-Generated) Artwork | Michaela Drouillard, Ryan Spencer, Nikée Nantambu-Allen, Tegan Maharaj |
| Epistemic Integrity in Large Language Models | Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou, Pratheeksha Nair, Jacob-Junqi Tian, Mayank Goel, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine |
| Bias Analysis in Unconditional Image Generative Models | Xiaofeng Zhang, Simon Lacoste-Julien, Aaron Courville, Yash Goyal |
| How Learning Rates Shape Neural Network Focus: Insights from Example Ranking | Ekaterina Lobacheva, Keller Jordan, Aristide Baratin, Nicolas Le Roux |
| Learning Stochastic Rainbow Networks | Vivian White, Muawiz Sajjad Chaudhary, Guy Wolf, Guillaume Lajoie, Kameron Decker Harris |
| Input Space Mode Connectivity in Deep Neural Networks | Jakub Vrabel, Ori Shem-Ur, Yaron Oz, David Krueger |
| The Pitfalls of Memorization: When Memorization Hinders Generalization | Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent |
| Language model scaling laws and zero-sum learning | Andrei Mircea, Ekaterina Lobacheva, Supriyo Chakraborty, Nima Chitsazan, Irina Rish |
| VCR: Visual Caption Restoration | Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio |
| Not All LLM Reasoners Are Created Equal | Arian Hosseini, Alessandro Sordoni, Daniel Toyama, Aaron Courville, Rishabh Agarwal |
| Introducing Brain Foundation Models | Mohammad Javad Darvishi Bayazi, Hena Ghonia, Roland Riachi, Bruno Aristimunha, Arian Khorasani, Md Rifat Arefin, Amin Darabi, Sylvain Chevallier, Guillaume Dumas, Irina Rish |
| TrajGPT: Healthcare Time-Series Representation Learning for Trajectory Prediction | Ziyang Song, Qincheng Lu, Mike He Zhu, David L. Buckeridge, Yue Li |
| Context is Key: A Benchmark for Forecasting with Essential Textual Information | Arjun Ashok, Andrew Robert Williams, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin |
| Understanding Permutation Based Model Merging with Feature Visualizations | Congshu Zou, geraldin nanfack, Stefan Horoi, Eugene Belilovsky |
| Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning | Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain |
| Zero-shot Whole-Body Humanoid Control via Behavioral Foundation Models | Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta |
| Safe Reinforcement Learning for Remote Microgrid Optimization with Industrial Constraints | Hadi Nekoei, Alexandre Blondin Massé, Rachid Hassani, Sarath Chandar, Vincent Mai |
| Towards Optimizing SQL Generation via LLM Routing | Mohammadhossein Malekpour, Nour Shaheen, Foutse Khomh, Amine Mhedhbi |
| Seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models | Hafez Ghaemi, Eilif Muller, Shahab Bakhtiari |
| CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept | YuXuan Wu, Bonaventure F. P. Dossou, Dianbo Liu |
| Visual Language Alignment Tuning | Le Zhang, Qian Yang, Aishwarya Agrawal |
| Casting hybrid digital-analog training into hierarchical energy-based learnng | Nest, Timothy; Ernoult, Maxence |
| Amortizing intractable inference in diffusion models for Bayesian inverse problems | 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, Yashar Hezaveh, Laurence Perreault-Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin |
| LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders | Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, Dzmitry Bahdanau, Nicolas Chapados, Siva Reddy |
| Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset | Khaoula Chehbouni*, Jonathan Colaço-Carr*, Yash More, Jackie Cheung, Golnoosh Farnadi |
| BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks | Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-Andre Noel, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Kurt MacDonald, Sathwik Tejaswi Madhusudhan, Joao Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharaghani, Sean Hughes, M. Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vazquez, Sai Rajeswar |
| MID-Space: Aligning Diverse Communities' Needs to Inclusive Public Spaces | Shravan Nayak, Rashid Mushkani, Hugo Berard, Allison Cohen, Shin Koseki, Hadrien Bertrand |
| TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers | Fatemeh Nourilenjan Nokabadi, Yann Batiste Pequignot, Jean-Francois Lalonde, Christian Gagné |
| Adversarial Bounding Boxes Generation (ABBG) Attack against Visual Object Trackers | Fatemeh Nourilenjan Nokabadi, Jean-Francois Lalonde, Christian Gagné |
| Symmetry-Aware Generative Modeling through Learned Canonicalization | Kusha Sareen, Daniel Levy, Arnab Kumar Mondal, Sékou-Oumar Kaba, Tara Akhound-Sadegh, Siamak Ravanbakhsh |
| PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction | A. Wenteler, M. Occhetta, N. Branson, M. Huebner, V. Curean, W. T. Dee, W. T. Connell, A. Hawkins-Hooker, S. P. Chung, Y. Ektefaie, A. Gallagher-Syed, C. M. V. Córdova |
| Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training | Hiroki Naganuma, Xinzhi Zhang, Man-Chung Yue, Ioannis Mitliagkas, Russell J. Hewett, Philipp Andre Witte, Yin Tat Lee |
| Mastering Task Arithmetic: τJp as a Key Indicator for Weight Disentanglement | Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian McAuley, Hiroki Naganuma |
| KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation | Rambod Azimi, Rishav Rishav, Marek Teichmann, Samira Ebrahimi Kahou |
| Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak Rebates | Julien Pallage, Bertrand Scherrer, Salma Naccache, Christophe Bélanger, Antoine Lesage-Landry |
| Controlling Multimodal LLMs via Reward-guided Decoding | Oscar Mañas, Pierluca D'Oro, Koustuv Sinha, Adriana Romero-Soriano, Michal Drozdzal, Aishwarya Agrawal |
| CTRL-O: Language-Controllable Object-Centric Visual Representation Learning | Aniket Didolkar*, Andrii Zadaianchuk*, Rabiul Awal*, Maximilian Seitzer, Efstratios Gavves, Aishwarya Agrawal |
| Enhancing Multi-Agent Multi-Modal Collaboration with Fine-Grained Reward Modeling | Qian Yang, Weixiang Yan, Aishwarya Agrawal |
| Solving hidden monotone variational inequalities with surrogate losses | Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel |
| Accelerated Stability in Performative Prediction | Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel |
| Adaptive Group Robust Ensemble Knowledge Distillation | Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou |
| The Data Minimization Principle in Machine Learning | Prakhar Ganesh, Cuong Tran, Reza Shokri, Ferdinando Fioretto |
| Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML | Prakhar Ganesh, Usman Gohar, Lu Cheng, Golnoosh Farnadi |
| Multilingual Hallucination Gaps in Large Language Models | Cléa Chataigner, Afaf Taïk, Golnoosh Farnadi |
| Correcting misspecified score-based priors for inverse problems: An application to strong gravitational lensing | Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur |
| Score-based models for 1/f correlated noise correction in James Webb Space Telescope spectral data | Salma Salhi, Alexandre Adam, Loïc Albert, René Doyon, Laurence Perreault-Levasseur |
| Accelerated Stability in Performative Prediction | Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel |
| EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics | Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K Yang, Guy Wolf, Doina Precup, Shuangjia Zheng |
| Compositional Risk Minimization | Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent |
| Zero-Shot Learning of Causal Models | Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon |
