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papers

Publications (104)

stat.ML2020

Learning Neural Causal Models from Unknown Interventions

Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal +6

cs.LG2019

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations

Alex Lamb, Jonathan Binas, Anirudh Goyal +5

cs.AI2024

Can AI Be as Creative as Humans?

Haonan Wang, James Zou, Michael Mozer +8

cs.LG2023

Discrete Key-Value Bottleneck

Frederik Träuble, Anirudh Goyal, Nasim Rahaman +4

cs.LG2021

On Disentangled Representations Learned From Correlated Data

Frederik Träuble, Elliot Creager, Niki Kilbertus +5

cs.LG2024

$α$-TCVAE: On the relationship between Disentanglement and Diversity

Cristian Meo, Louis Mahon, Anirudh Goyal +1

cs.LG2021

Fast and Slow Learning of Recurrent Independent Mechanisms

Kanika Madan, Nan Rosemary Ke, Anirudh Goyal +2

cs.SE2026

Scaling Test-Time Compute for Agentic Coding

Joongwon Kim, Wannan Yang, Kelvin Niu +13

cs.RO2020

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ossama Ahmed, Frederik Träuble, Anirudh Goyal +5

cs.CL2024

Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling

Yiran Zhao, Wenyue Zheng, Tianle Cai +4

stat.ML2018

Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations

Alex Lamb, Jonathan Binas, Anirudh Goyal +4

cs.LG2020

Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Anirudh Goyal, Alex Lamb, Phanideep Gampa +5

cs.LG2019

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

Yoshua Bengio, Tristan Deleu, Nasim Rahaman +5

stat.ML2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net

Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli +1

cs.AI2017

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks

Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk +4

cs.LG2025

On the Impossibility of Retrain Equivalence in Machine Unlearning

Jiatong Yu, Yinghui He, Anirudh Goyal +1

cs.LG2026

Auto-Discovery-Bench: Diagnosing Structured State Tracking in Oracle-Guided Discovery

Tingting Chen, Beibei Lin, Srinivas Anumasa +5

cs.LG2025

Masked Generative Priors Improve World Models Sequence Modelling Capabilities

Cristian Meo, Mircea Lica, Zarif Ikram +6

cs.LG2022

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning

Riashat Islam, Hongyu Zang, Anirudh Goyal +6

stat.ML2022

Learning to Induce Causal Structure

Nan Rosemary Ke, Silvia Chiappa, Jane Wang +7

cs.LG2023

A Theory for Emergence of Complex Skills in Language Models

Sanjeev Arora, Anirudh Goyal

cs.LG2022

Inductive Biases for Deep Learning of Higher-Level Cognition

Anirudh Goyal, Yoshua Bengio

cs.CL2024

COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement

Yuxi Xie, Anirudh Goyal, Xiaobao Wu +5

cs.LG2020

S2RMs: Spatially Structured Recurrent Modules

Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal +5

cs.CL2024

Reasoning Robustness of LLMs to Adversarial Typographical Errors

Esther Gan, Yiran Zhao, Liying Cheng +5

cs.CV2023

Cycle Consistency Driven Object Discovery

Aniket Didolkar, Anirudh Goyal, Yoshua Bengio

stat.ML2019

Small-GAN: Speeding Up GAN Training Using Core-sets

Samarth Sinha, Han Zhang, Anirudh Goyal +3

stat.ML2022

Learning Neural Causal Models with Active Interventions

Nino Scherrer, Olexa Bilaniuk, Yashas Annadani +7

cs.CV2023

Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior

Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal +2

cs.LG2026

Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models

Xingyu Dang, Rohit Agarwal, Rodrigo Porto +3

cs.CV2015

Stories in the Eye: Contextual Visual Interactions for Efficient Video to Language Translation

Anirudh Goyal, Marius Leordeanu

cs.LG2025

Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning

Simon Frieder, Jonas Bayer, Sam Looi +13

cs.AI2024

Physical Reasoning and Object Planning for Household Embodied Agents

Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal +1

cs.LG2026

Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision

Dulhan Jayalath, Shashwat Goel, Thomas Foster +5

cs.CV2024

Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak +1

cs.CL2025

Unnatural Languages Are Not Bugs but Features for LLMs

Keyu Duan, Yiran Zhao, Zhili Feng +9

stat.ML2023

InfoBot: Transfer and Exploration via the Information Bottleneck

Anirudh Goyal, Riashat Islam, Daniel Strouse +5

cs.LG2025

Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning

Simran Kaur, Simon Park, Anirudh Goyal +1

cs.LG2020

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers

Alex Lamb, Anirudh Goyal, Agnieszka Słowik +3

cs.CL2025

Can Models Learn Skill Composition from Examples?

Haoyu Zhao, Simran Kaur, Dingli Yu +2

cs.AI2022

Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel

Dianbo Liu, Vedant Shah, Oussama Boussif +6

cs.LG2021

Discrete-Valued Neural Communication

Dianbo Liu, Alex Lamb, Kenji Kawaguchi +4

cs.LG2020

Diversity inducing Information Bottleneck in Model Ensembles

Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal +3

cs.LG2023

Representation Learning in Deep RL via Discrete Information Bottleneck

Riashat Islam, Hongyu Zang, Manan Tomar +8

stat.ML2020

Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples

Samarth Sinha, Zhengli Zhao, Anirudh Goyal +2

cs.CV2023

Leveraging the Third Dimension in Contrastive Learning

Sumukh Aithal, Anirudh Goyal, Alex Lamb +2

cs.CL2025

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Rohan Anil, Sebastian Borgeaud +1340

cs.CV2024

Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases

Cristian Meo, Akihiro Nakano, Mircea Lică +7

cs.AI2026

The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

Alejandro H. Artiles, Martin Weiss, Levin Brinkmann +6

cs.AI2024

Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs

Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke +3

cs.LG2020

Recurrent Independent Mechanisms

Anirudh Goyal, Alex Lamb, Jordan Hoffmann +4

cs.AI2024

Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Yuxi Xie, Anirudh Goyal, Wenyue Zheng +4

cs.LG2018

Generalization of Equilibrium Propagation to Vector Field Dynamics

Benjamin Scellier, Anirudh Goyal, Jonathan Binas +2

stat.ML2017

ACtuAL: Actor-Critic Under Adversarial Learning

Anirudh Goyal, Nan Rosemary Ke, Alex Lamb +4

stat.ML2017

Z-Forcing: Training Stochastic Recurrent Networks

Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté +2

cs.LG2025

Metacognitive Reuse: Turning Recurring LLM Reasoning Into Concise Behaviors

Aniket Didolkar, Nicolas Ballas, Sanjeev Arora +1

cs.LG2019

Recall Traces: Backtracking Models for Efficient Reinforcement Learning

Anirudh Goyal, Philemon Brakel, William Fedus +5

cs.CL2026

HypoSpace: A Diagnostic Benchmark for Set-Valued Hypothesis Generation under Underdetermination and Sublinear Coverage Bounds

Tingting Chen, Beibei Lin, Zifeng Yuan +5

cs.CV2023

Test-time Adaptation with Slot-Centric Models

Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul +6

cs.DB2026

Experience Graphs: The Data Foundation for Self-Improving Agents

Gang Liao, Yujia He, Abdullah Ozturk +22

cs.AI2024

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 +1

cs.CV2024

Zero-Shot Object-Centric Representation Learning

Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal +4

cs.LG2022

Coordination Among Neural Modules Through a Shared Global Workspace

Anirudh Goyal, Aniket Didolkar, Alex Lamb +7

cs.LG2017

An Actor-Critic Algorithm for Sequence Prediction

Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu +5

cs.AI2025

ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context

Joongwon Kim, Anirudh Goyal, Liang Tan +3

cs.AI2025

AI-Assisted Generation of Difficult Math Questions

Vedant Shah, Dingli Yu, Kaifeng Lyu +8

cs.LG2024

Narrowing the Focus: Learned Optimizers for Pretrained Models

Gus Kristiansen, Mark Sandler, Andrey Zhmoginov +4

cs.LG2022

Retrieval-Augmented Reinforcement Learning

Anirudh Goyal, Abram L. Friesen, Andrea Banino +13

cs.CL2023

Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models

Dingli Yu, Simran Kaur, Arushi Gupta +3

cs.LG2026

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

Qiran Zou, Hou Hei Lam, Wenhao Zhao +11

cs.LG2022

On the Generalization and Adaption Performance of Causal Models

Nino Scherrer, Anirudh Goyal, Stefan Bauer +2

cs.LG2020

Uniform Priors for Data-Efficient Transfer

Samarth Sinha, Karsten Roth, Anirudh Goyal +3

cs.CL2024

A Systematic Examination of Preference Learning through the Lens of Instruction-Following

Joongwon Kim, Anirudh Goyal, Aston Zhang +6

cs.AI2023

Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning

Dianbo Liu, Vedant Shah, Oussama Boussif +6

cs.AI2022

Neural Production Systems: Learning Rule-Governed Visual Dynamics

Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke +5

cs.LG2019

Learning Powerful Policies by Using Consistent Dynamics Model

Shagun Sodhani, Anirudh Goyal, Tristan Deleu +3

cs.LG2023

GFlowOut: Dropout with Generative Flow Networks

Dianbo Liu, Moksh Jain, Bonaventure Dossou +10

cs.LG2020

Untangling tradeoffs between recurrence and self-attention in neural networks

Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal +3

cs.CV2025

Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?

Simon Park, Abhishek Panigrahi, Yun Cheng +3

cs.LG2025

Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Kaifeng Lyu, Haoyu Zhao, Xinran Gu +3

cs.LG2021

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures

Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste +4

cs.LG2025

Rethinking Thinking Tokens: LLMs as Improvement Operators

Lovish Madaan, Aniket Didolkar, Suchin Gururangan +6

cs.LG2020

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

Sarthak Mittal, Alex Lamb, Anirudh Goyal +5

cs.LG2018

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding

Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk +4

cs.LG2021

Towards Causal Representation Learning

Bernhard Schölkopf, Francesco Locatello, Stefan Bauer +4

q-bio.MN2023

DiscoGen: Learning to Discover Gene Regulatory Networks

Nan Rosemary Ke, Sara-Jane Dunn, Jorg Bornschein +11

cs.LG2021

Robust Representation Learning via Perceptual Similarity Metrics

Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi +1

stat.ML2016

Professor Forcing: A New Algorithm for Training Recurrent Networks

Alex Lamb, Anirudh Goyal, Ying Zhang +3

cs.RO2022

Real Robot Challenge: A Robotics Competition in the Cloud

Stefan Bauer, Felix Widmaier, Manuel Wüthrich +39

cs.AI2025

SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement

Antonis Antoniades, Albert Örwall, Kexun Zhang +3

stat.ML2021

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal +7

cs.LG2024

Unlearning via Sparse Representations

Vedant Shah, Frederik Träuble, Ashish Malik +5

cs.NE2017

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

David Krueger, Tegan Maharaj, János Kramár +7

cs.LG2022

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning

Aniket Didolkar, Kshitij Gupta, Anirudh Goyal +4

stat.ML2020

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Anirudh Goyal, Yoshua Bengio, Matthew Botvinick +1

cs.LG2020

Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning

Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey +4

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

cs.LG2023

TC-VAE: Uncovering Out-of-Distribution Data Generative Factors

Cristian Meo, Anirudh Goyal, Justin Dauwels

cs.LG2021

Transformers with Competitive Ensembles of Independent Mechanisms

Alex Lamb, Di He, Anirudh Goyal +4

cs.LG2019

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives

Anirudh Goyal, Shagun Sodhani, Jonathan Binas +3