Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. - Chunjong Park; Anas Awadalla; Tadayoshi Kohno; Shwetak N. Patel (NeurIPS, 2021)

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)

VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (NeurIPS, 2023)

Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text. - Wanrong Zhu; Jack Hessel; Anas Awadalla; Samir Yitzhak Gadre; Jesse Dodge; Alex Fang; Youngjae Yu; Ludwig Schmidt; William Yang Wang; Yejin Choi 001 (NeurIPS, 2023)

Are aligned neural networks adversarially aligned? - Nicholas Carlini; Milad Nasr; Christopher A. Choquette-Choo; Matthew Jagielski; Irena Gao; Anas Awadalla; Pang Wei Koh; Daphne Ippolito; Katherine Lee; Florian Tramèr; Ludwig Schmidt (CoRR, 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)

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (CoRR, 2023)

Catwalk: A Unified Language Model Evaluation Framework for Many Datasets. - Dirk Groeneveld; Anas Awadalla; Iz Beltagy; Akshita Bhagia; Ian Magnusson; Hao Peng 009; Oyvind Tafjord; Pete Walsh; Kyle Richardson 001; Jesse Dodge (CoRR, 2023)

xGen-VideoSyn-1: High-Fidelity Text-to-Video Synthesis with Compressed Representations. - Can Qin; Congying Xia; Krithika Ramakrishnan; Michael S. Ryoo; Lifu Tu; Yihao Feng; Manli Shu; Honglu Zhou; Anas Awadalla; Jun Wang 090; Senthil Purushwalkam; Le Xue; et al. (ECCV Workshops (5), 2024)

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. - Anas Awadalla; Le Xue; Oscar Lo; Manli Shu; Hannah Lee; Etash Kumar Guha; Sheng Shen 001; Mohamed Awadalla; Silvio Savarese; Caiming Xiong; Ran Xu 001; Yejin Choi 001; et al. (NeurIPS, 2024)

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. - Anas Awadalla; Le Xue; Oscar Lo; Manli Shu; Hannah Lee; Etash Kumar Guha; Matt Jordan; Sheng Shen 001; Mohamed Awadalla; Silvio Savarese; Caiming Xiong; Ran Xu 001; et al. (CoRR, 2024)

Certainly Uncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. - Khyathi Raghavi Chandu; Linjie Li; Anas Awadalla; Ximing Lu; Jae Sung Park; Jack Hessel; Lijuan Wang; Yejin Choi 001 (CoRR, 2024)

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models. - Le Xue; Manli Shu; Anas Awadalla; Jun Wang 090; An Yan; Senthil Purushwalkam; Honglu Zhou; Viraj Prabhu; Yutong Dai 002; Michael S. Ryoo; Shrikant Kendre; Jieyu Zhang 001; et al. (CoRR, 2024)

BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions. - Anas Awadalla; Le Xue; Manli Shu; An Yan; Jun Wang 090; Senthil Purushwalkam; Sheng Shen 001; Hannah Lee; Oscar Lo; Jae Sung Park; Etash Kumar Guha; Silvio Savarese; et al. (CoRR, 2024)

CertainlyUncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. - Khyathi Raghavi Chandu; Linjie Li; Anas Awadalla; Ximing Lu; Jae Sung Park; Jack Hessel; Lijuan Wang; Yejin Choi 001 (ICLR, 2025)