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publications

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The Promise of RL for Autoregressive Image Editing
Saba Ahmadi*, Rabiul Awal*, Ankur Sikarwar*, Amirhossein Kazemnejad*, Ge Ya Luo, Juan A. Rodriguez, Sai Rajeswar, Siva Reddy, Christopher Pal, Benno Krojer, Aishwarya Agrawal (* Denotes equal contribution)

NeurIPS 2025

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When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks
Ankur Sikarwar, Arkil Patel, Navin Goyal

EMNLP 2022 [Oral]

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Learning to Learn: How to Continuously Teach Humans and Machines
Parantak Singh, You Li, Ankur Sikarwar, Weixan Lei, Daniel Gao, Morgan Bruce Talbot,
Ying Sun, Mike Zheng Shou, Gabriel Kreiman, Mengmi Zhang

ICCV 2023

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Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory

Ankur Sikarwar, Mengmi Zhang

NeurIPS 2023, Datasets and Benchmarks Track

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Reason from Context with Self-supervised Learning
Xiao Liu, Ankur Sikarwar, Joo Hwee Lim, Gabriel Kreiman, Zenglin Shi, Mengmi Zhang

In Review

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Human or Machine? Turing Tests for Vision and Language

Mengmi Zhang, Giorgia Dellaferrera, Ankur Sikarwar, Marcelo Armendariz, Noga Mudrik, Prachi Agrawal, Spandan Madan, Mranmay Shetty, Andrei Barbu, Haochen Yang, Tanishq Kumar, Shui’Er Han, Aman Raj Singh, Meghna Sadwani, Stella Dellaferrera, Michele Pizzochero, Brandon Tang, Hanspeter Pfister, Gabriel Kreiman

In Review

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On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering

Ankur Sikarwar, Gabriel Kreiman

Preprint

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