Progress and Limitations of Deep Networks to Recognize Objects in Unusual Poses. - Amro Abbas; Stéphane Deny (AAAI, 2023)

SemDeDup: Data-efficient learning at web-scale through semantic deduplication. - Amro Abbas; Kushal Tirumala; Daniel Simig; Surya Ganguli; Ari S. Morcos (CoRR, 2023)

Sieve: Multimodal Dataset Pruning Using Image Captioning Models. - Anas Mahmoud 002; Mostafa Elhoushi; Amro Abbas; Yu Yang; Newsha Ardalani; Hugh Leather; Ari S. Morcos (CVPR, 2024)

Effective pruning of web-scale datasets based on complexity of concept clusters. - Amro Abbas; Evgenia Rusak; Kushal Tirumala; Wieland Brendel; Kamalika Chaudhuri; Ari S. Morcos (ICLR, 2024)

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)

Humans Beat Deep Networks at Recognizing Objects in Unusual Poses, Given Enough Time. - Netta Ollikka; Amro Abbas; Andrea Perin; Markku Kilpeläinen; Stéphane Deny (CoRR, 2024)

A comparison between humans and AI at recognizing objects in unusual poses. - Netta Ollikka; Amro Abbas; Andrea Perin; Markku Kilpeläinen; Stéphane Deny (Trans. Mach. Learn. Res., 2025)