Aishwarya Agrawal -- Home

Publications

	How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning Qian Yang, Ankur Sikarwar, Huy Le, Le Zhang, Zhuan Shi, Perouz Taslakian, Aishwarya Agrawal *equal contribution ArXiv preprint, arXiv:2605.27310, 2026 [ArXiv]
	RiT: Vanilla Diffusion Transformers Suffice in Representation Space Le Zhang, Ning Mang, Aishwarya Agrawal ArXiv preprint, arXiv:2605.21981, 2026 [ArXiv]
	Communicating about Space: Language-Mediated Spatial Integration Across Partial Views Ankur Sikarwar, Debangan Mishra, Sudarshan Nikhil, Ponnurangam Kumaraguru, Aishwarya Agrawal *equal contribution ArXiv preprint, arXiv:2603.27183, 2026 [ArXiv]
	Discovering Failure Modes in Vision–Language Models using RL Kanishk Jain, Qian Yang, Shravan Nayak, Parisa Kordjamshidi, Nishanth Anand, Aishwarya Agrawal *equal contribution ArXiv preprint, arXiv:2604.04733, 2026 [ArXiv]
	Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selection Shivam Chandhok, Qian Yang, Oscar Manas, Kanishk Jain, Leonid Sigal^, Aishwarya Agrawal^ *equal first author contribution ^equal last author contribution CVPR 2026 [ArXiv]
	From Where Things Are to What They Are For: Benchmarking SpatialFunctional Intelligence in Multimodal LLMs. Le Zhang, Jihan Yang, Soundarya Krishnan, Jimit Majmudar, Xiou Ge, Prasoon Puri, Prathamesh Saraf, Shruti Bhargava, Dhivya Piraviperumal, Yinan Ling, Cindy Pan, Hong Yu, Aishwarya Agrawal, Bo-Hsiang Tseng CVPR 2026 [ArXiv]
	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 *equal first author contribution NeurIPS 2025 [ArXiv]
	REARANK: Reasoning Re-ranking Agent via Reinforcement Learning Le Zhang, Bo Wang, Xipeng Qiu, Siva Reddy, Aishwarya Agrawal EMNLP 2025 [ArXiv]
	CulturalFrames: Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics Shravan Nayak, Mehar Bhatia, Xiaofeng Zhang, Verena Rieser, Lisa Anne Hendricks, Sjoerd van Steenkiste, Yash Goyal, Karolina Stańczak,, Aishwarya Agrawal EMNLP Findings 2025 [ArXiv]
	WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation Rabiul Awal, Mahsa Massoud, Aarash Feizi^, Zichao Li^, Suyuchen Wang, Christopher Pal, Aishwarya Agrawal, David Vazquez, Siva Reddy, Juan A. Rodriguez, Perouz Taslakian, Spandana Gella, Sai Rajeswar *co-first authors ^co-second authors EMNLP 2025 [ArXiv]
	Controlling Multimodal LLMs via Reward-guided Decoding Oscar Mañas, Pierluca D'Oro, Koustuv Sinha, Adriana Romero-Soriano, Michal Drozdzal, Aishwarya Agrawal ICCV 2025 [ArXiv]
	UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Juan A. Rodriguez, Montek Kalsi, Rabiul Awal, Nicolas Chapados, M. Tamer Özsu, Aishwarya Agrawal, David Vazquez, Christopher Pal, Perouz Taslakian, Spandana Gella, Sai Rajeswar *equal first author contribution ICML 2025 [ArXiv]
	CTRL-O: Language-Controllable Object-Centric Visual Representation Learning Aniket Didolkar, Andrii Zadaianchuk^, Rabiul Awal, Maximilian Seitzer, Efstratios Gavves, Aishwarya Agrawal^ equal first author contribution ^equal last author contribution CVPR 2025 [ArXiv]
	Assessing and Learning Alignment of Unimodal Vision and Language Models Le Zhang, Qian Yang, Aishwarya Agrawal CVPR 2025 [Highlight Poster] [ArXiv]
	Improving Text-to-Image Consistency via Automatic Prompt Optimization Oscar Mañas, Pietro Astolfi, Melissa Hall, Candace Ross, Jack Urbanek, Adina Williams, Aishwarya Agrawal, Adriana Romero-Soriano, Michal Drozdzal TMLR 2024 [Featured Certification] [ArXiv]
	VisMin: Visual Minimal-Change Understanding Rabiul Awal, Saba Ahmadi, Le Zhang, Aishwarya Agrawal equal contribution NeurIPS 2024 [ArXiv]
	Investigating Prompting Techniques for Zero- and Few-Shot Visual Question Answering Rabiul Awal, Le Zhang, Aishwarya Agrawal Multimodal Algorithmic Reasoning Workshop, NeurIPS 2024 [ArXiv]
	Benchmarking Vision Language Models for Cultural Understanding Shravan Nayak, Kanishk Jain, Rabiul Awal, Siva Reddy, Sjoerd van Steenkiste, Lisa Anne Hendricks, Karolina Stanczak, Aishwarya Agrawal EMNLP 2024 [Oral] [ArXiv]
	Decompose and Compare Consistency: Measuring VLMs’ Answer Reliability via Task-Decomposition Consistency Comparison Qian Yang, Weixiang Yan, Aishwarya Agrawal EMNLP 2024 [ArXiv]
	An Introduction to Vision-Language Modeling Florian Bordes et al. arXiv preprint, arXiv:2405.17247, 2024 [ArXiv]
	Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional Understanding Le Zhang, Rabiul Awal, Aishwarya Agrawal CVPR 2024 [ArXiv]
	An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics Saba Ahmadi, Aishwarya Agrawal EACL Findings 2024 [ArXiv]
	Improving Automatic VQA Evaluation Using Large Language Models Oscar Mañas,, Benno Krojer, Aishwarya Agrawal AAAI 2024 [ArXiv]
	MoqaGPT: Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model Le Zhang, Yihong Wu, Fengran Mo, Jian-Yun Nie, Aishwarya Agrawal EMNLP Findings 2023 [ArXiv]
	Measuring Progress in Fine-grained Vision-and-Language Understanding Emanuele Bugliarello, Laurent Sartran, Aishwarya Agrawal, Lisa Anne Hendricks, Aida Nematzadeh ACL 2023 [ArXiv]
	MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting Oscar Mañas, Pau Rodríguez, Saba Ahmadi, Aida Nematzadeh, Yash Goyal, Aishwarya Agrawal equal contribution EACL 2023 [Oral*] [ArXiv \| Code \| Live Demo]
	Rethinking Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization Aishwarya Agrawal, Ivana Kajić, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh (see paper for equal contributions) EACL Findings 2023 [ArXiv]
	Visual Question Answering and Beyond Aishwarya Agrawal PhD Dissertation, 2019 [PDF]
	Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning Aishwarya Agrawal, Mateusz Malinowski, Felix Hill, Ali Eslami, Oriol Vinyals, Tejas Kulkarni Visually-Grounded Interaction and Language Workshop, (spotlight), NIPS 2018 Learning by Instruction Workshop, NIPS 2018 [ArXiv]
	Overcoming Language Priors in Visual Question Answering with Adversarial Regularization Sainandan Ramakrishnan, Aishwarya Agrawal, Stefan Lee NIPS 2018 [ArXiv]
	Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering Aishwarya Agrawal, Dhruv Batra, Devi Parikh, Aniruddha Kembhavi CVPR 2018 [ArXiv \| Project Page]
	Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes Gordon Christie, Ankit Laddha, Aishwarya Agrawal, Stanislaw Antol, Yash Goyal, Kevin Kochersberger, Dhruv Batra *equal contribution Computer Vision and Image Understanding (CVIU) Journal, 2017 [Arxiv \| Project Page]
	C-VQA: A Compositional Split of the Visual Question Answering (VQA) v1.0 Dataset Aishwarya Agrawal, Aniruddha Kembhavi, Dhruv Batra, Devi Parikh arXiv preprint, arXiv:1704.08243, 2017 [ArXiv]
	VQA: Visual Question Answering Aishwarya Agrawal, Jiasen Lu, Stanislaw Antol, Margaret Mitchell, Larry Zitnick, Devi Parikh, Dhruv Batra equal contribution Special Issue on Combined Image and Language Understanding, International Journal of Computer Vision (IJCV), 2017 [ ArXiv \| visualqa.org (data, code, challenge) \| slides \| talk at GPU Technology Conference (GTC) 2016]
	Analyzing the Behavior of Visual Question Answering Models Aishwarya Agrawal, Dhruv Batra, Devi Parikh EMNLP 2016 [Arxiv \| slides \| talk at Deep Learning Summer School, Montreal, 2016]
	Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes Gordon Christie, Ankit Laddha, Aishwarya Agrawal, Stanislaw Antol, Yash Goyal, Kevin Kochersberger, Dhruv Batra *equal contribution EMNLP 2016 [Arxiv \| Project Page]
	Measuring Machine Intelligence Through Visual Question Answering Larry Zitnick, Aishwarya Agrawal, Stanislaw Antol, Margaret Mitchell, Dhruv Batra, Devi Parikh AI Magazine, 2016 [Paper \| ArXiv]
	Visual Storytelling Ting-Hao Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, Larry Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, Margaret Mitchell NAACL 2016 [Arxiv, Project Page]
	VQA: Visual Question Answering Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, Larry Zitnick, Devi Parikh *equal contribution ICCV 2015 [ ICCV Camera Ready Paper \| ArXiv \| ICCV Spotlight \| visualqa.org (data, code, challenge) \| slides \| talk at GPU Technology Conference (GTC) 2016]
	A Novel LBP Based Operator for Tone Mapping HDR Images Aishwarya Agrawal, Shanmuganathan Raman International Conference on Signal Processing and Communications (SPCOM-2014) [Paper \|Poster]
	Optically clearing tissue as an initial step for 3D imaging of core biopsies to diagnose pancreatic cancer Ronnie Das, Aishwarya Agrawal, Melissa P. Upton, Eric J. Seibel SPIE BiOS, International Society for Optics and Photonics, 2014 [Paper]

Videos and Talks

For a full list of my talks, please check my CV.

Advancing multimodal vision-language learning
Area Chair Workshop @ CVPR (June, 2024). [slides]
Understanding LLM Understanding Summer School (June, 2024). [slides | Watch].
CIFAR AICan Retreat (June, 2024). [slides]
World Summit AI Americas (April, 2023). [slides | Watch]
Text in Everything workshop @ ECCV (Oct, 2022). [slides]
Tea Talks @ Mila (Sep, 2022). [slides | Watch].
Visual-Language Learning [slides]
Tutorial on Visual Recognition Beyond the Comfort Zone: Adapting to Unseen Concepts on the Fly @ ICCV (Oct, 2023). [Watch].
Career Panel
CIFAR Deep Learning + Reinforcement Learning Summer School (July, 2023).
Roundtable lead: Robustness
Montreal AI Symposium (MAIS) (Sep, 2022).
Are current Vision-language models learning to solve the task or merely learning to solve the dataset [slides]
Tea Talks @ Mila (Feb, 2022). [Watch].
Vision and Language: Progress and Challenges [slides]
Research Week with Google (India) (Feb, 2022).
Montreal AI Symposium (October, 2021). [Watch] (start - 1.00.00).
Microsoft Research, Montreal (September, 2021).
Panel: Paths to Leadership in Data Science
Women in Data Science (WiDS) Conference (March, 2021).
[Watch]
My journey with Artificial Intelligence so far [slides]
Women in Computer Vision Workshop , CVPR 2021 (June, 2021).
Alumni MasterClass @ Indian Institute of Technology (IIT) Gandhinagar (July, 2020). [Watch]
Visual Grounding in Visual Question Answering [slides]
GeCKo Symposium, 2020.
[Watch]
Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering [slides]
Women in Computer Vision workshop, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[Watch] (32:33 - 56:08)
Winner announcements, analysis of results [slides]
VQA Challenge Workshop 2017, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[Watch] (47:22 - 1:07:09)
Analyzing the Behavior of Deep Visual Question Answering Models [slides]
Deep Learning Summer School, Montreal, 2016.
[Watch]
Overview of challenge, winner announcements, analysis of results [slides]
VQA Challenge Workshop, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
[Watch]
Visual Question Answering [slides]
GPU Technology Conference (GTC), 2016.
[Watch]
Visual Question Answering
Spotlight at International Conference on Computer Vision (ICCV), 2015.
[Watch]

Aishwarya Agrawal

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Videos and Talks