| 2026 | CHI | Presenting Large Language Models as Companions Affects What Mental Capacities People Attribute to Them. | Allison Chen, Sunnie S. Y. Kim, Angel Nathaniel Franyutti-Cintron, Amaya Dharmasiri, Kushin Mukherjee, Olga Russakovsky, Judith E. Fan |
| 2025 | CHI | 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 |
| 2025 | CHI | 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 |
| 2025 | CHI | 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 |
| 2025 | CogSci | Portraying Large Language Models as Machines, Tools, or Companions Affects What Mental Capacities People Attribute to Them. | Allison Chen, Sunnie S. Y. Kim, Amaya Dharmasiri, Olga Russakovsky, Judith E. Fan |
| 2025 | CogSci | Learning a Doubly-Exponential Number of Concepts From Few Examples. | Ilia Sucholutsky, Bonan Zhao, Hee Seung Hwang, Allison Chen, Olga Russakovsky, Tom Griffiths |
| 2025 | CVPR | Attention IoU: Examining Biases in CelebA using Attention Maps. | Aaron Serianni, Tyler Zhu, Olga Russakovsky, Vikram V. Ramaswamy |
| 2025 | CVPR | D^3: Scaling Up Deepfake Detection by Learning from Discrepancy. | Yongqi Yang, Zhihao Qian, Ye Zhu, Olga Russakovsky, Yu Wu |
| 2025 | ICCV | The Silent Assistant: NoiseQuery as Implicit Guidance for Goal-Driven Image Generation. | Ruoyu Wang, Huayang Huang, Ye Zhu, Olga Russakovsky, Yu Wu |
| 2025 | ICML | Unifying Specialized Visual Encoders for Video Language Models. | Jihoon Chung, Tyler Zhu, Max Gonzalez Saez-Diez, Juan Carlos Niebles, Honglu Zhou, Olga Russakovsky |
| 2024 | CogSci | Analyzing the Roles of Language and Vision in Learning from Limited Data. | Allison Chen, Ilia Sucholutsky, Olga Russakovsky, Tom Griffiths |
| 2024 | ICLR | ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms. | William Yang, Byron Zhang, Olga Russakovsky |
| 2024 | ICML | What is Dataset Distillation Learning? | William Yang, Ye Zhu, Zhiwei Deng, Olga Russakovsky |
| 2023 | CHI | "Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction. | Sunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, Andrs Monroy-Hernndez |
| 2023 | CogSci | Predicting Word Learning in Children from the Performance of Computer Vision Systems. | Sunayana Rane, Mira L. Nencheva, Zeyu Wang, Casey Lew-Williams, Olga Russakovsky, Tom Griffiths |
| 2023 | CVPR | Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability. | Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky |
| 2023 | ICCV | Gender Artifacts in Visual Datasets. | Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky |
| 2023 | ICCV | Overwriting Pretrained Bias with Finetuning Data. | Angelina Wang, Olga Russakovsky |
| 2022 | ACL | CARETS: A Consistency And Robustness Evaluative Test Suite for VQA. | Carlos E. Jimenez, Olga Russakovsky, Karthik Narasimhan |
| 2022 | ECCV | HIVE: Evaluating the Human Interpretability of Visual Explanations. | Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky |
| 2022 | ECCV | SiRi: A Simple Selective Retraining Mechanism for Transformer-Based Visual Grounding. | Mengxue Qu, Yu Wu, Wu Liu, Qiqi Gong, Xiaodan Liang, Olga Russakovsky, Yao Zhao, Yunchao Wei |
| 2022 | ECCV | Multi-query Video Retrieval. | Zeyu Wang, Yu Wu, Karthik Narasimhan, Olga Russakovsky |
| 2022 | ICML | A Study of Face Obfuscation in ImageNet. | Kaiyu Yang, Jacqueline H. Yau, Li Fei-Fei, Jia Deng, Olga Russakovsky |
| 2021 | CVPR | Fair Attribute Classification Through Latent Space De-Biasing. | Vikram V. Ramaswamy, Sunnie S. Y. Kim, Olga Russakovsky |
| 2021 | ICCV | Understanding and Evaluating Racial Biases in Image Captioning. | Dora Zhao, Angelina Wang, Olga Russakovsky |
| 2021 | ICML | Directional Bias Amplification. | Angelina Wang, Olga Russakovsky |
| 2020 | BMVC | CornerNet-Lite: Efficient Keypoint based Object Detection. | Hei Law, Yun Teng, Olga Russakovsky, Jia Deng |
| 2020 | CVPR | Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation. | Zeyu Wang, Klint Qinami, Ioannis Christos Karakozis, Kyle Genova, Prem Nair, Kenji Hata, Olga Russakovsky |
| 2020 | CVPR | Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation. | Felix Yu, Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky |
| 2020 | ECCV | Towards Unique and Informative Captioning of Images. | Zeyu Wang, Berthy Feng, Karthik Narasimhan, Olga Russakovsky |
| 2020 | ECCV | REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. | Angelina Wang, Arvind Narayanan, Olga Russakovsky |
| 2019 | ICCV | Human Uncertainty Makes Classification More Robust. | Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, Olga Russakovsky |
| 2019 | ICCV | SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition. | Kaiyu Yang, Olga Russakovsky, Jia Deng |
| 2018 | WACV | The More You Look, the More You See: Towards General Object Understanding Through Recursive Refinement. | Jingyan Wang, Olga Russakovsky, Deva Ramanan |
| 2017 | CVPR | Predictive-Corrective Networks for Action Detection. | Achal Dave, Olga Russakovsky, Deva Ramanan |
| 2017 | CVPR | What's in a Question: Using Visual Questions as a Form of Supervision. | Siddha Ganju, Olga Russakovsky, Abhinav Gupta |
| 2017 | CVPR | Learning to Learn from Noisy Web Videos. | Serena Yeung, Vignesh Ramanathan, Olga Russakovsky, Liyue Shen, Greg Mori, Li Fei-Fei |
| 2017 | ICCV | What Actions are Needed for Understanding Human Actions in Videos? | Gunnar A. Sigurdsson, Olga Russakovsky, Abhinav Gupta |
| 2016 | CVPR | End-to-End Learning of Action Detection from Frame Glimpses in Videos. | Serena Yeung, Olga Russakovsky, Greg Mori, Li Fei-Fei |
| 2016 | ECCV | What's the Point: Semantic Segmentation with Point Supervision. | Amy L. Bearman, Olga Russakovsky, Vittorio Ferrari, Li Fei-Fei |
| 2016 | HCOMP | Much Ado About Time: Exhaustive Annotation of Temporal Data. | Gunnar A. Sigurdsson, Olga Russakovsky, Ali Farhadi, Ivan Laptev, Abhinav Gupta |
| 2016 | SIGCSE | 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 |
| 2015 | CVPR | Joint calibration of Ensemble of Exemplar SVMs. | Davide Modolo, Alexander Vezhnevets, Olga Russakovsky, Vittorio Ferrari |
| 2015 | CVPR | Best of both worlds: Human-machine collaboration for object annotation. | Olga Russakovsky, Li-Jia Li, Li Fei-Fei |
| 2014 | CHI | Scalable multi-label annotation. | Jia Deng, Olga Russakovsky, Jonathan Krause, Michael S. Bernstein, Alexander C. Berg, Li Fei-Fei |
| 2013 | ICCV | Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going? | Olga Russakovsky, Jia Deng, Zhiheng Huang, Alexander C. Berg, Li Fei-Fei |
| 2012 | ECCV | Object-Centric Spatial Pooling for Image Classification. | Olga Russakovsky, Yuanqing Lin, Kai Yu, Li Fei-Fei |
| 2010 | CVPR | A Steiner tree approach to efficient object detection. | Olga Russakovsky, Andrew Y. Ng |
| 2010 | ECCV | Attribute Learning in Large-Scale Datasets. | Olga Russakovsky, Li Fei-Fei |
| 2010 | ICRA | Autonomous operation of novel elevators for robot navigation. | Ellen Klingbeil, Blake Carpenter, Olga Russakovsky, Andrew Y. Ng |