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Antonio Torralba

MIT EECS professor; pioneer in computer vision, scene understanding, and multimodal representation learning.

Role
professor
Currently at
MIT CSAIL
Papers
29

Cite

Notes

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29papers

Authored papers

29

MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and Retrieval

arXiv 2026

2026

Ambient Diffusion Omni: Training Good Models with Bad Data

arXiv 2025

2025

SketchAgent: Language-Driven Sequential Sketch Generation

CVPR 2025 1

2024

MMToM-QA: Multimodal Theory of Mind Question Answering

arXiv 2024

2024

A Multimodal Automated Interpretability Agent

arXiv 2024

2024

Improving Factuality and Reasoning in Language Models through Multiagent Debate

arXiv 2023

2023

Follow Anything: Open-set detection, tracking, and following in real-time

arXiv 2023

2023

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

arXiv 2023

2023

Debiasing Vision-Language Models via Biased Prompts

arXiv 2023

2023

Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models

arXiv 2023

2023

FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation

arXiv 2023

2023

FIND: A Function Description Benchmark for Evaluating Interpretability Methods

find-a-function-description-benchmark-for

2023

Dataset Distillation by Matching Training Trajectories

CVPR 2022 1

2022

Compositional Visual Generation with Composable Diffusion Models

arXiv 2022

2022

Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents

arXiv 2022

2022

Denoised MDPs: Learning World Models Better Than the World Itself

arXiv 2022

2022

Procedural Image Programs for Representation Learning

arXiv 2022

2022

$BT^2$: Backward-compatible Training with Basis Transformation

arXiv 2022

2022

Ego4D: Around the World in 3,000 Hours of Egocentric Video

CVPR 2022 1

2021

Learning to See by Looking at Noise

NeurIPS 2021 12

2021

Toward a Visual Concept Vocabulary for GAN Latent Space

toward-a-visual-concept-vocabulary-for-gan

2021

Debiased Contrastive Learning

NeurIPS 2020 12

2020

Understanding the Role of Individual Units in a Deep Neural Network

arXiv 2020

2020

Rewriting a Deep Generative Model

ECCV 2020 8

2020

Diverse Image Generation via Self-Conditioned GANs

diverse-image-generation-via-self-conditioned

2020

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

gan-dissection-visualizing-and-understanding-1

2018

Dataset Distillation

arXiv 2018

2018

Network Dissection: Quantifying Interpretability of Deep Visual Representations

network-dissection-quantifying-1

2017

Semantic Understanding of Scenes through the ADE20K Dataset

arXiv 2016

2016

Affiliations

Currently at

MIT CSAIL

professor · university lab

Frequent co-authors

10

from 29 papers