Training Conditional Random Fields for Maximum Labelwise Accuracy. - Samuel S. Gross; Olga Russakovsky; Chuong B. Do; Serafim Batzoglou (NIPS, 2006)

A Steiner tree approach to efficient object detection. - Olga Russakovsky; Andrew Y. Ng (CVPR, 2010)

Attribute Learning in Large-Scale Datasets. - Olga Russakovsky; Li Fei-Fei 001 (ECCV Workshops (1), 2010)

Autonomous operation of novel elevators for robot navigation. - Ellen Klingbeil; Blake Carpenter; Olga Russakovsky; Andrew Y. Ng (ICRA, 2010)

Object-Centric Spatial Pooling for Image Classification. - Olga Russakovsky; Yuanqing Lin; Kai Yu 001; Li Fei-Fei 001 (ECCV (2), 2012)

Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going? - Olga Russakovsky; Jia Deng 001; Zhiheng Huang; Alexander C. Berg; Li Fei-Fei 001 (ICCV, 2013)

Scalable multi-label annotation. - Jia Deng 001; Olga Russakovsky; Jonathan Krause; Michael S. Bernstein; Alexander C. Berg; Li Fei-Fei 001 (CHI, 2014)

Joint calibration of Ensemble of Exemplar SVMs. - Davide Modolo; Alexander Vezhnevets; Olga Russakovsky; Vittorio Ferrari (CVPR, 2015)

Best of both worlds: Human-machine collaboration for object annotation. - Olga Russakovsky; Li-Jia Li 001; Li Fei-Fei 001 (CVPR, 2015)

ImageNet Large Scale Visual Recognition Challenge. - Olga Russakovsky; Jia Deng 001; Hao Su 001; Jonathan Krause; Sanjeev Satheesh; Sean Ma; Zhiheng Huang; Andrej Karpathy; Aditya Khosla; Michael S. Bernstein; Alexander C. Berg; Li Fei-Fei 001 (Int. J. Comput. Vis., 2015)

Scaling up object detection. - Olga Russakovsky (2015)

End-to-End Learning of Action Detection from Frame Glimpses in Videos. - Serena Yeung; Olga Russakovsky; Greg Mori; Li Fei-Fei 001 (CVPR, 2016)

What's the Point: Semantic Segmentation with Point Supervision. - Amy L. Bearman; Olga Russakovsky; Vittorio Ferrari; Li Fei-Fei 001 (ECCV (7), 2016)

Much Ado About Time: Exhaustive Annotation of Temporal Data. - Gunnar A. Sigurdsson; Olga Russakovsky; Ali Farhadi; Ivan Laptev; Abhinav Gupta 001 (HCOMP, 2016)

Toward More Gender Diversity in CS through an Artificial Intelligence Summer Program for High School Girls. - Marie E. Vachovsky; Grace Wu; Sorathan Chaturapruek; Olga Russakovsky; Richard Sommer; Li Fei-Fei 001 (SIGCSE, 2016)

Crowdsourcing in Computer Vision. - Adriana Kovashka; Olga Russakovsky; Li Fei-Fei 001; Kristen Grauman (Found. Trends Comput. Graph. Vis., 2016)

Predictive-Corrective Networks for Action Detection. - Achal Dave; Olga Russakovsky; Deva Ramanan (CVPR, 2017)

What's in a Question: Using Visual Questions as a Form of Supervision. - Siddha Ganju; Olga Russakovsky; Abhinav Gupta 001 (CVPR, 2017)

Learning to Learn from Noisy Web Videos. - Serena Yeung; Vignesh Ramanathan; Olga Russakovsky; Liyue Shen; Greg Mori; Li Fei-Fei 001 (CVPR, 2017)

What Actions are Needed for Understanding Human Actions in Videos? - Gunnar A. Sigurdsson; Olga Russakovsky; Abhinav Gupta 001 (ICCV, 2017)

The More You Look, the More You See: Towards General Object Understanding Through Recursive Refinement. - Jingyan Wang 001; Olga Russakovsky; Deva Ramanan (WACV, 2018)

Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos. - Serena Yeung; Olga Russakovsky; Ning Jin 002; Mykhaylo Andriluka; Greg Mori; Li Fei-Fei 001 (Int. J. Comput. Vis., 2018)

Human Uncertainty Makes Classification More Robust. - Joshua C. Peterson; Ruairidh M. Battleday; Thomas L. Griffiths 001; Olga Russakovsky (ICCV, 2019)

SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition. - Kaiyu Yang; Olga Russakovsky; Jia Deng 001 (ICCV, 2019)

Compositional Temporal Visual Grounding of Natural Language Event Descriptions. - Jonathan C. Stroud; Ryan McCaffrey; Rada Mihalcea; Jia Deng 001; Olga Russakovsky (CoRR, 2019)

CornerNet-Lite: Efficient Keypoint based Object Detection. - Hei Law; Yun Teng; Olga Russakovsky; Jia Deng 001 (BMVC, 2020)

Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation. - Zeyu Wang 004; Klint Qinami; Ioannis Christos Karakozis; Kyle Genova; Prem Nair; Kenji Hata; Olga Russakovsky (CVPR, 2020)

Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation. - Felix Yu; Zhiwei Deng; Karthik Narasimhan; Olga Russakovsky (CVPR Workshops, 2020)

Towards Unique and Informative Captioning of Images. - Zeyu Wang 004; Berthy Feng; Karthik Narasimhan; Olga Russakovsky (ECCV (7), 2020)

REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. - Angelina Wang; Arvind Narayanan; Olga Russakovsky (ECCV (3), 2020)

Towards fairer datasets: filtering and balancing the distribution of the people subtree in the ImageNet hierarchy. - Kaiyu Yang; Klint Qinami; Li Fei-Fei 001; Jia Deng 001; Olga Russakovsky (FAT*, 2020)

Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation. - Zhiwei Deng; Karthik Narasimhan; Olga Russakovsky (NeurIPS, 2020)

ViBE: A Tool for Measuring and Mitigating Bias in Image Datasets. - Angelina Wang; Arvind Narayanan; Olga Russakovsky (CoRR, 2020)

Point and Ask: Incorporating Pointing into Visual Question Answering. - Arjun Mani; Will Hinthorn; Nobline Yoo; Olga Russakovsky (CoRR, 2020)

Fair Attribute Classification Through Latent Space De-Biasing. - Vikram V. Ramaswamy; Sunnie S. Y. Kim; Olga Russakovsky (CVPR, 2021)

Understanding and Evaluating Racial Biases in Image Captioning. - Dora Zhao; Angelina Wang; Olga Russakovsky (ICCV, 2021)

Directional Bias Amplification. - Angelina Wang; Olga Russakovsky (ICML, 2021)

[Re] Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias. - Sunnie S. Y. Kim; Sharon Zhang; Nicole Meister; Olga Russakovsky (CoRR, 2021)

CARETS: A Consistency And Robustness Evaluative Test Suite for VQA. - Carlos E. Jimenez; Olga Russakovsky; Karthik Narasimhan (ACL (1), 2022)

HIVE: Evaluating the Human Interpretability of Visual Explanations. - Sunnie S. Y. Kim; Nicole Meister; Vikram V. Ramaswamy; Ruth Fong; Olga Russakovsky (ECCV (12), 2022)

SiRi: A Simple Selective Retraining Mechanism for Transformer-Based Visual Grounding. - Mengxue Qu; Yu Wu 011; Wu Liu; Qiqi Gong; Xiaodan Liang; Olga Russakovsky; Yao Zhao 001; Yunchao Wei (ECCV (35), 2022)

Multi-query Video Retrieval. - Zeyu Wang 004; Yu Wu 011; Karthik Narasimhan; Olga Russakovsky (ECCV (14), 2022)

Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. - Angelina Wang; Vikram V. Ramaswamy; Olga Russakovsky (FAccT, 2022)

A Study of Face Obfuscation in ImageNet. - Kaiyu Yang; Jacqueline H. Yau; Li Fei-Fei 001; Jia Deng 001; Olga Russakovsky (ICML, 2022)

Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation. - Jihoon Chung; Yu Wu 011; Olga Russakovsky (NeurIPS, 2022)

Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks. - Zhiwei Deng; Olga Russakovsky (NeurIPS, 2022)

ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features. - Vikram V. Ramaswamy; Sunnie S. Y. Kim; Nicole Meister; Ruth Fong; Olga Russakovsky (CoRR, 2022)

Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability. - Vikram V. Ramaswamy; Sunnie S. Y. Kim; Ruth Fong; Olga Russakovsky (CoRR, 2022)

REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. - Angelina Wang; Alexander Liu; Ryan Zhang; Anat Kleiman; Leslie Kim; Dora Zhao; Iroha Shirai; Arvind Narayanan; Olga Russakovsky (Int. J. Comput. Vis., 2022)

"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction. - Sunnie S. Y. Kim; Elizabeth Anne Watkins; Olga Russakovsky; Ruth Fong; Andrés Monroy-Hernández (CHI, 2023)

Predicting Word Learning in Children from the Performance of Computer Vision Systems. - Sunayana Rane; Mira L. Nencheva; Zeyu Wang 004; Casey Lew-Williams; Olga Russakovsky; Tom Griffiths 001 (CogSci, 2023)

Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability. - Vikram V. Ramaswamy; Sunnie S. Y. Kim; Ruth Fong; Olga Russakovsky (CVPR, 2023)

Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application. - Sunnie S. Y. Kim; Elizabeth Anne Watkins; Olga Russakovsky; Ruth Fong; Andrés Monroy-Hernández (FAccT, 2023)

Gender Artifacts in Visual Datasets. - Nicole Meister; Dora Zhao; Angelina Wang; Vikram V. Ramaswamy; Ruth Fong; Olga Russakovsky (ICCV, 2023)

Overwriting Pretrained Bias with Finetuning Data. - Angelina Wang; Olga Russakovsky (ICCV, 2023)

Efficient, Self-Supervised Human Pose Estimation with Inductive Prior Tuning. - Nobline Yoo; Olga Russakovsky (ICCV (Workshops), 2023)

GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition. - Vikram V. Ramaswamy; Sing Yu Lin; Dora Zhao; Aaron Adcock; Laurens van der Maaten; Deepti Ghadiyaram; Olga Russakovsky (NeurIPS, 2023)

Boundary Guided Learning-Free Semantic Control with Diffusion Models. - Ye Zhu; Yu Wu 011; Zhiwei Deng; Olga Russakovsky; Yan Yan 002 (NeurIPS, 2023)

Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset. - Vikram V. Ramaswamy; Sing Yu Lin; Dora Zhao; Aaron B. Adcock; Laurens van der Maaten; Deepti Ghadiyaram; Olga Russakovsky (CoRR, 2023)

Boundary Guided Mixing Trajectory for Semantic Control with Diffusion Models. - Ye Zhu; Yu Wu 011; Zhiwei Deng; Olga Russakovsky; Yan Yan 002 (CoRR, 2023)

Overcoming Bias in Pretrained Models by Manipulating the Finetuning Dataset. - Angelina Wang; Olga Russakovsky (CoRR, 2023)

UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs. - Vikram V. Ramaswamy; Sunnie S. Y. Kim; Ruth Fong; Olga Russakovsky (CoRR, 2023)

Art and the science of generative AI: A deeper dive. - Ziv Epstein; Aaron Hertzmann; Laura Mariah Herman; Robert Mahari; Morgan R. Frank; Matthew Groh; Hope Schroeder; Amy Smith; Memo Akten; Jessica Fjeld; Hany Farid; Neil Leach; et al. (CoRR, 2023)

ICON2: Reliably Benchmarking Predictive Inequity in Object Detection. - Sruthi Sudhakar; Viraj Prabhu; Olga Russakovsky; Judy Hoffman (CoRR, 2023)

Multimodal Dataset Distillation for Image-Text Retrieval. - Xindi Wu; Zhiwei Deng; Olga Russakovsky (CoRR, 2023)

Unseen Image Synthesis with Diffusion Models. - Ye Zhu; Yu Wu 011; Zhiwei Deng; Olga Russakovsky; Yan Yan 002 (CoRR, 2023)

DETER: Detecting Edited Regions for Deterring Generative Manipulations. - Sai Wang; Ye Zhu; Ruoyu Wang 034; Amaya Dharmasiri; Olga Russakovsky; Yu Wu 011 (CoRR, 2023)

Learning actionness from action/background discrimination. - Ozge Yalcinkaya Simsek; Olga Russakovsky; Pinar Duygulu (Signal Image Video Process., 2023)

ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms. - William Yang; Byron Zhang; Olga Russakovsky (ICLR, 2024)

What is Dataset Distillation Learning? - William Yang; Ye Zhu; Zhiwei Deng; Olga Russakovsky (ICML, 2024)

ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty. - Xindi Wu; Dingli Yu; Yangsibo Huang; Olga Russakovsky; Sanjeev Arora (NeurIPS, 2024)

Analyzing the Roles of Language and Vision in Learning from Limited Data. - Allison Chen; Ilia Sucholutsky; Olga Russakovsky; Thomas L. Griffiths 001 (CoRR, 2024)

SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation. - Yuhan Pei; Ruoyu Wang 034; Yongqi Yang; Ye Zhu; Olga Russakovsky; Yu Wu 011 (CoRR, 2024)

The Silent Prompt: Initial Noise as Implicit Guidance for Goal-Driven Image Generation. - Ruoyu Wang 034; Huayang Huang; Ye Zhu; Olga Russakovsky; Yu Wu 011 (CoRR, 2024)

Benchmark suites instead of leaderboards for evaluating AI fairness. - Angelina Wang; Aaron Hertzmann; Olga Russakovsky (Patterns, 2024)

Vision-Language Dataset Distillation. - Xindi Wu; Byron Zhang; Zhiwei Deng; Olga Russakovsky (Trans. Mach. Learn. Res., 2024)

Portraying Large Language Models as Machines, Tools, or Companions Affects What Mental Capacities Humans Attribute to Them. - Allison Chen; Sunnie S. Y. Kim; Amaya Dharmasiri; Olga Russakovsky; Judith E. Fan (CHI Extended Abstracts, 2025)

Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies. - Sunnie S. Y. Kim; Jennifer Wortman Vaughan; Q. Vera Liao; Tania Lombrozo; Olga Russakovsky (CHI, 2025)

Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations. - Indu Panigrahi; Sunnie S. Y. Kim; Amna Liaqat; Rohan Jinturkar; Olga Russakovsky; Ruth Fong; Parastoo Abtahi (CHI Extended Abstracts, 2025)

Attention IoU: Examining Biases in CelebA using Attention Maps. - Aaron Serianni; Tyler Zhu; Olga Russakovsky; Vikram V. Ramaswamy (CVPR, 2025)

D^3: Scaling Up Deepfake Detection by Learning from Discrepancy. - Yongqi Yang; Zhihao Qian; Ye Zhu; Olga Russakovsky; Yu Wu 011 (CVPR, 2025)

ICONS: Influence Consensus for Vision-Language Data Selection. - Xindi Wu; Mengzhou Xia; Rulin Shao; Zhiwei Deng; Pang Wei Koh; Olga Russakovsky (CoRR, 2025)

Unifying Specialized Visual Encoders for Video Language Models. - Jihoon Chung; Tyler Zhu; Max Gonzalez Saez-Diez; Juan Carlos Niebles; Honglu Zhou; Olga Russakovsky (CoRR, 2025)

COMPACT: COMPositional Atomic-to-Complex Visual Capability Tuning. - Xindi Wu; Hee Seung Hwang; Polina Kirichenko; Olga Russakovsky (CoRR, 2025)

Dynamic Diffusion Schrödinger Bridge in Astrophysical Observational Inversions. - Ye Zhu; Duo Xu 005; Zhiwei Deng; Jonathan C. Tan; Olga Russakovsky (CoRR, 2025)

The Impact of Coreset Selection on Spurious Correlations and Group Robustness. - Amaya Dharmasiri; William Yang; Polina Kirichenko; Lydia Liu; Olga Russakovsky (CoRR, 2025)