Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation. - Vihan Jain; Gabriel Magalhães 001; Alexander Ku; Ashish Vaswani; Eugene Ie; Jason Baldridge (ACL (1), 2019)

Large-Scale Representation Learning from Visually Grounded Untranscribed Speech. - Gabriel Ilharco; Yuan Zhang 001; Jason Baldridge (CoNLL, 2019)

Transferable Representation Learning in Vision-and-Language Navigation. - Haoshuo Huang; Vihan Jain; Harsh Mehta; Alexander Ku; Gabriel Magalhães 001; Jason Baldridge; Eugene Ie (ICCV, 2019)

General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping. - Gabriel Ilharco; Vihan Jain; Alexander Ku; Eugene Ie; Jason Baldridge (ViGIL@NeurIPS, 2019)

Evaluating Models' Local Decision Boundaries via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hannaneh Hajishirzi; et al. (EMNLP (Findings), 2020)

High Performance Natural Language Processing. - Gabriel Ilharco; Cesar Ilharco; Iulia Turc; Tim Dettmers; Felipe Ferreira; Kenton Lee (EMNLP (Tutorial Abstracts), 2020)

Toward ML-centric cloud platforms. - Ricardo Bianchini; Marcus Fontoura; Eli Cortez; Anand Bonde; Alexandre Muzio; Ana-Maria Constantin; Thomas Moscibroda; Gabriel Magalhães 001; Girish Bablani; Mark Russinovich (Commun. ACM, 2020)

Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping. - Jesse Dodge; Gabriel Ilharco; Roy Schwartz 001; Ali Farhadi; Hannaneh Hajishirzi; Noah A. Smith (CoRR, 2020)

Evaluating NLP Models via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hanna Hajishirzi; et al. (CoRR, 2020)

Probing Text Models for Common Ground with Visual Representations. - Gabriel Ilharco; Rowan Zellers; Ali Farhadi; Hannaneh Hajishirzi (CoRR, 2020)

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus. - Jesse Dodge; Maarten Sap; Ana Marasovic; William Agnew; Gabriel Ilharco; Dirk Groeneveld; Margaret Mitchell; Matt Gardner 001 (EMNLP (1), 2021)

Finetuning Pretrained Transformers into RNNs. - Jungo Kasai; Hao Peng 009; Yizhe Zhang 002; Dani Yogatama; Gabriel Ilharco; Nikolaos Pappas 002; Yi Mao; Weizhu Chen; Noah A. Smith (EMNLP (1), 2021)

Contrasting Contrastive Self-Supervised Representation Learning Pipelines. - Klemen Kotar; Gabriel Ilharco; Ludwig Schmidt; Kiana Ehsani; Roozbeh Mottaghi (ICCV, 2021)

MultiModalQA: complex question answering over text, tables and images. - Alon Talmor; Ori Yoran; Amnon Catav; Dan Lahav; Yizhong Wang; Akari Asai; Gabriel Ilharco; Hannaneh Hajishirzi; Jonathan Berant (ICLR, 2021)

Probing Contextual Language Models for Common Ground with Visual Representations. - Gabriel Ilharco; Rowan Zellers; Ali Farhadi; Hannaneh Hajishirzi (NAACL-HLT, 2021)

Contrasting Contrastive Self-Supervised Representation Learning Models. - Klemen Kotar; Gabriel Ilharco; Ludwig Schmidt; Kiana Ehsani; Roozbeh Mottaghi (CoRR, 2021)

Documenting the English Colossal Clean Crawled Corpus. - Jesse Dodge; Maarten Sap; Ana Marasovic; William Agnew; Gabriel Ilharco; Dirk Groeneveld; Matt Gardner 001 (CoRR, 2021)

Robust fine-tuning of zero-shot models. - Mitchell Wortsman; Gabriel Ilharco; Mike Li; Jong Wook Kim; Hannaneh Hajishirzi; Ali Farhadi; Hongseok Namkoong; Ludwig Schmidt (CoRR, 2021)

Robust fine-tuning of zero-shot models. - Mitchell Wortsman; Gabriel Ilharco; Jong Wook Kim; Mike Li; Simon Kornblith; Rebecca Roelofs; Raphael Gontijo Lopes; Hannaneh Hajishirzi; Ali Farhadi; Hongseok Namkoong; Ludwig Schmidt (CVPR, 2022)

Exploring The Landscape of Distributional Robustness for Question Answering Models. - Anas Awadalla; Mitchell Wortsman; Gabriel Ilharco; Sewon Min; Ian Magnusson; Hannaneh Hajishirzi; Ludwig Schmidt (EMNLP (Findings), 2022)

Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP). - Alex Fang; Gabriel Ilharco; Mitchell Wortsman; Yuhao Wan; Vaishaal Shankar; Achal Dave; Ludwig Schmidt (ICML, 2022)

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. - Mitchell Wortsman; Gabriel Ilharco; Samir Yitzhak Gadre; Rebecca Roelofs; Raphael Gontijo Lopes; Ari S. Morcos; Hongseok Namkoong; Ali Farhadi; Yair Carmon; Simon Kornblith; Ludwig Schmidt (ICML, 2022)

Patching open-vocabulary models by interpolating weights. - Gabriel Ilharco; Mitchell Wortsman; Samir Yitzhak Gadre; Shuran Song; Hannaneh Hajishirzi; Simon Kornblith; Ali Farhadi; Ludwig Schmidt (NeurIPS, 2022)

Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. - Thao Nguyen; Gabriel Ilharco; Mitchell Wortsman; Sewoong Oh; Ludwig Schmidt (NeurIPS, 2022)

CLIP on Wheels: Zero-Shot Object Navigation as Object Localization and Exploration. - Samir Yitzhak Gadre; Mitchell Wortsman; Gabriel Ilharco; Ludwig Schmidt; Shuran Song (CoRR, 2022)

Editing Models with Task Arithmetic. - Gabriel Ilharco; Marco Túlio Ribeiro; Mitchell Wortsman; Suchin Gururangan; Ludwig Schmidt; Hannaneh Hajishirzi; Ali Farhadi (CoRR, 2022)

Reproducible Scaling Laws for Contrastive Language-Image Learning. - Mehdi Cherti; Romain Beaumont; Ross Wightman; Mitchell Wortsman; Gabriel Ilharco; Cade Gordon; Christoph Schuhmann; Ludwig Schmidt; Jenia Jitsev (CVPR, 2023)

CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation. - Samir Yitzhak Gadre; Mitchell Wortsman; Gabriel Ilharco; Ludwig Schmidt; Shuran Song (CVPR, 2023)

TaskWeb: Selecting Better Source Tasks for Multi-task NLP. - Joongwon Kim; Akari Asai; Gabriel Ilharco; Hannaneh Hajishirzi (EMNLP, 2023)

Adaptive Testing of Computer Vision Models. - Irena Gao; Gabriel Ilharco; Scott M. Lundberg; Marco Túlio Ribeiro (ICCV, 2023)

Editing models with task arithmetic. - Gabriel Ilharco; Marco Túlio Ribeiro; Mitchell Wortsman; Ludwig Schmidt; Hannaneh Hajishirzi; Ali Farhadi (ICLR, 2023)

DataComp: In search of the next generation of multimodal datasets. - Samir Yitzhak Gadre; Gabriel Ilharco; Alex Fang; Jonathan Hayase; Georgios Smyrnis; Thao Nguyen; Ryan Marten; Mitchell Wortsman; Dhruba Ghosh; Jieyu Zhang 001; Eyal Orgad; Rahim Entezari; et al. (NeurIPS, 2023)

Improving multimodal datasets with image captioning. - Thao Nguyen; Samir Yitzhak Gadre; Gabriel Ilharco; Sewoong Oh; Ludwig Schmidt (NeurIPS, 2023)

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. - Anas Awadalla; Irena Gao; Josh Gardner 001; Jack Hessel; Yusuf Hanafy; Wanrong Zhu; Kalyani Marathe; Yonatan Bitton; Samir Yitzhak Gadre; Shiori Sagawa; Jenia Jitsev; Simon Kornblith; et al. (CoRR, 2023)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Language models scale reliably with over-training and on downstream tasks. - Samir Yitzhak Gadre; Georgios Smyrnis; Vaishaal Shankar; Suchin Gururangan; Mitchell Wortsman; Rulin Shao; Jean Mercat; Alex Fang; Jeffrey Li; Sedrick Keh; Rui Xin; Marianna Nezhurina; et al. (CoRR, 2024)

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. - Shayne Longpre; Stella Biderman; Alon Albalak; Hailey Schoelkopf; Daniel McDuff; Sayash Kapoor; Kevin Klyman; Kyle Lo; Gabriel Ilharco; Nay San; Maribeth Rauh; Aviya Skowron; et al. (Trans. Mach. Learn. Res., 2024)

Building the Next Generation of Multimodal Models - Gabriel Ilharco (2024)

Language models scale reliably with over-training and on downstream tasks. - Samir Yitzhak Gadre; Georgios Smyrnis; Vaishaal Shankar; Suchin Gururangan; Mitchell Wortsman; Rulin Shao; Jean Mercat; Alex Fang; Jeffrey Li; Sedrick Keh; Rui Xin; Marianna Nezhurina; et al. (ICLR, 2025)