Goyal, Anirudh

68 publications

ICML 2025 Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? Simon Park, Abhishek Panigrahi, Yun Cheng, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ICLRW 2025 Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? Simon Park, Abhishek Panigrahi, Yun Cheng, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ICLR 2025 Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora

TMLR 2025 Low Compute Unlearning via Sparse Representations Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Curtis Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal

ICLRW 2025 Masked Generative Priors Improve World Models Sequence Modelling Capabilities Cristian Meo, Mircea Tudor Lică, Zarif Ikram, Akihiro Nakano, Vedant Shah, Aniket Rajiv Didolkar, Dianbo Liu, Anirudh Goyal, Justin Dauwels

ICLR 2025 On the Transfer of Object-Centric Representation Learning Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer

ICLR 2025 SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang

ICLR 2025 Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron Yiran Zhao, Wenxuan Zhang, Yuxi Xie, Anirudh Goyal, Kenji Kawaguchi, Michael Shieh

ICML 2025 Unnatural Languages Are Not Bugs but Features for LLMs Keyu Duan, Yiran Zhao, Zhili Feng, Jinjie Ni, Tianyu Pang, Qian Liu, Tianle Cai, Longxu Dou, Kenji Kawaguchi, Anirudh Goyal, J Zico Kolter, Michael Qizhe Shieh

ICLRW 2025 Unnatural Languages Are Not Bugs but Features for LLMs Keyu Duan, Yiran Zhao, Zhili Feng, Jinjie Ni, Tianyu Pang, Qian Liu, Tianle Cai, Longxu Dou, Kenji Kawaguchi, Anirudh Goyal, J Zico Kolter, Michael Qizhe Shieh

ICLR 2024 $\alpha$TC-VAE: On the Relationship Between Disentanglement and Diversity Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels

NeurIPSW 2024 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

NeurIPS 2024 Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Qizhe Shieh

ICMLW 2024 Bayesian-LoRA: LoRA Based Parameter Efficient Fine-Tuning Using Optimal Quantization Levels and Rank Values Trough Differentiable Bayesian Gates Cristian Meo, Ksenia Sycheva, Anirudh Goyal, Justin Dauwels

NeurIPSW 2024 COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement Yuxi Xie, Anirudh Goyal, Xiaobao Wu, Xunjian Yin, Xiao Xu, Min-Yen Kan, Liangming Pan, William Yang Wang

NeurIPS 2024 Can Models Learn Skill Composition from Examples? Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ICMLW 2024 Can Models Learn Skill Composition from Examples? Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora

NeurIPSW 2024 Can Models Learn Skill Composition from Examples? Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ICLR 2024 Cycle Consistency Driven Object Discovery Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio

NeurIPSW 2024 Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora

NeurIPSW 2024 Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora

NeurIPS 2024 Keeping LLMs Aligned After Fine-Tuning: The Crucial Role of Prompt Templates Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ICLRW 2024 Keeping LLMs Aligned After Fine-Tuning: The Crucial Role of Prompt Templates Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora

NeurIPS 2024 Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy Lillicrap, Danilo Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora

ICMLW 2024 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

NeurIPSW 2024 Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P Lillicrap, Kenji Kawaguchi, Michael Shieh

NeurIPSW 2024 Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases Cristian Meo, Akihiro Nakano, Mircea Tudor Lică, Aniket Rajiv Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio

TMLR 2024 Physical Reasoning and Object Planning for Household Embodied Agents Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu

ICLR 2024 SKILL-MIX: A Flexible and Expandable Family of Evaluations for AI Models Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora

ICML 2023 Discrete Key-Value Bottleneck Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf

ICML 2023 GFlowOut: Dropout with Generative Flow Networks 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

ICLR 2023 Learning to Induce Causal Structure Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Theophane Weber, Matthew Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende

TMLR 2023 Neural Causal Structure Discovery from Interventions Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio

AISTATS 2023 Representation Learning in Deep RL via Discrete Information Bottleneck Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb

NeurIPSW 2023 Skill-Mix: A Flexible and Expandable Family of Evaluations for AI Models Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora

ICLR 2023 Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio

ICML 2023 Test-Time Adaptation with Slot-Centric Models Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul, Sjoerd Van Steenkiste, Mehdi S. M. Sajjadi, Gaurav Aggarwal, Thomas Kipf, Deepak Pathak, Katerina Fragkiadaki

ICLR 2022 Coordination Among Neural Modules Through a Shared Global Workspace Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio

NeurIPS 2022 Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes

ICLR 2022 Learning by Directional Gradient Descent David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt

ICMLW 2022 Learning to Induce Causal Structure Nan Rosemary Ke, Silvia Chiappa, Jane X Wang, Jorg Bornschein, Anirudh Goyal, Melanie Rey, Matthew Botvinick, Theophane Weber, Michael Curtis Mozer, Danilo Jimenez Rezende

ICMLW 2022 On the Generalization and Adaption Performance of Causal Models Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke

ICML 2022 Retrieval-Augmented Reinforcement Learning Anirudh Goyal, Abram Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter C Humphreys, Ksenia Konyushova, Michal Valko, Simon Osindero, Timothy Lillicrap, Nicolas Heess, Charles Blundell

NeurIPS 2022 Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh Bharadwaj Gundavarapu, Alex M Lamb, Nan Rosemary Ke, Yoshua Bengio

NeurIPSW 2022 Test-Time Adaptation with Slot-Centric Models Mihir Prabhudesai, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki, Gaurav Aggarwal, Thomas Kipf

NeurIPSW 2022 Test-Time Adaptation with Slot-Centric Models Mihir Prabhudesai, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki, Gaurav Aggarwal, Thomas Kipf

CVPRW 2022 Uniform Priors for Data-Efficient Learning Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg

AISTATS 2021 Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information Across Layers Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio

ICLR 2021 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer

AAAI 2021 DIBS: Diversity Inducing Information Bottleneck in Model Ensembles Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti

ICLR 2021 Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer

ICLR 2021 Fast and Slow Learning of Recurrent Independent Mechanisms Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio

ICML 2021 On Disentangled Representations Learned from Correlated Data Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer

ICLR 2021 Recurrent Independent Mechanisms Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf

ICML 2021 Robust Representation Learning via Perceptual Similarity Metrics Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal

ICLR 2021 Spatially Structured Recurrent Modules Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf

ICLR 2020 A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher Pal

ICLR 2020 Learning the Arrow of Time for Problems in Reinforcement Learning Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio

ICML 2020 Learning to Combine Top-Down and Bottom-up Signals in Recurrent Neural Networks with Attention over Modules Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

ICLR 2020 Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio

ICML 2020 Small-GAN: Speeding up GAN Training Using Core-Sets Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena

ICLR 2020 The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

ICLR 2019 InfoBot: Transfer and Exploration via the Information Bottleneck Anirudh Goyal, Riashat Islam, Dj Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew Botvinick, Yoshua Bengio, Sergey Levine

ICLR 2019 Modeling the Long Term Future in Model-Based Reinforcement Learning Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

ICLR 2019 Recall Traces: Backtracking Models for Efficient Reinforcement Learning Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio

ICML 2019 State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer

ICLR 2017 An Actor-Critic Algorithm for Sequence Prediction Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio

ICLR 2017 Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal