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Agneet Chatterjee
I am a Computer Science PhD candidate at Arizona State University, advised by
Chitta Baral and
Yezhou Yang.
My research focuses on controllable image and video generative models.
During my PhD, I interned at
Google,
Adobe Research, and
Stability AI.
Before my PhD, I was a software engineer at
Salesforce.
I will graduate in 2026 and am looking for industry positions focused on generative image and video models.
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News
- July, 2026 - Joined Adobe Research as a Research Intern, post-training video generative models for character control.
- March, 2026 - Joined Google as a Student Researcher, aligning video models for cinematic and geometric control.
- February, 2026 - Passed my PhD Candidacy Exam!
- September, 2025 - Stable Cinemetrics is out and will be presented at NeurIPS 2025!
- September, 2025 - 1 paper accepted at TMLR.
- September, 2025 - 1 paper accepted at EMNLP 2025.
- June, 2025 - Best paper award at CVPR BEAM Workshop 2025.
- January, 2025 - Joined Stability AI as a Research Scientist Intern to work on video generative models.
- July, 2024 - SPRIGHT and REVISION accepted to ECCV 2024!
- April, 2024 - New preprint out. More details on our website.
- March, 2024 - 1 paper accepted to NAACL 2024.
- March, 2024 - Received travel grants from SCAI and GPSA.
- February, 2024 - 1 paper accepted to CVPR 2024!
- February, 2024 - Received the SCAI Doctoral Fellowship.
- March, 2023 - Received the SCAI Engineering Fellowship.
- January, 2023 - Started my PhD.
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Stable Cinemetrics: Structured Taxonomy and Evaluation for Professional Video Generation
Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Max Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, Varun Jampani
NeurIPS 2025
Paper | Project
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AcT2I: Evaluating and Improving Action Depiction in Text-to-Image Models
Vatsal Malaviya, Agneet Chatterjee, Maitreya Patel, Yezhou Yang, Chitta Baral
EMNLP 2025 (Main)
Paper
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Dual Caption Preference Optimization for Diffusion Models
Amir Saeidi, Yiran Luo, Agneet Chatterjee, Shamanthak Hegde, Bimsara Pathiraja, Yezhou Yang, Chitta Baral
TMLR
Paper
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TextInVision: Text and Prompt Complexity Driven Visual Text Generation Benchmark
Forouzan Fallah, Maitreya Patel, Agneet Chatterjee, Vlad Morariu, Chitta Baral, Yezhou Yang
CVPR BEAM Workshop 2025 | Best Paper Award
Paper
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Getting it Right: Improving Spatial Consistency in Text-to-Image Models
Agneet Chatterjee*, Gabriela Ben Melech Stan*, Estelle Aflalo, Sayak Paul, Dhruba Ghosh, Tejas Gokhale, Ludwig Schmidt, Hannaneh Hajishirzi, Vasudev Lal, Chitta Baral, Yezhou Yang
ECCV 2024
Paper | Project | Code
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REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models
Agneet Chatterjee*, Yiran Luo*, Tejas Gokhale, Yezhou Yang, Chitta Baral
ECCV 2024
Paper | Project | Data | Code
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On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation
Agneet Chatterjee, Tejas Gokhale, Chitta Baral, Yezhou Yang
CVPR 2024
Paper | Project | Code
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Evaluating Multimodal Large Language Models Across Distribution Shifts and Augmentations
Aayush Atul Verma*, Amir Saeidi*, Shamanthak Hegde*, Ajay Therala*, Fenil Denish Bardoliya*, Nagaraju Machavarapu*, Shri Ajay Kumar Ravindhiran*, Srija Malyala*, Agneet Chatterjee*, Yezhou Yang, Chitta Baral
CVPR 2024 Workshop - Evaluation of Generative Foundation Models
Paper
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Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation
Neeraj Varshney, Satyam Raj, Venkatesh Mishra, Agneet Chatterjee, Ritika Sarkar, Amir Saeidi, Chitta Baral
NAACL TrustNLP 2025 Workshop
Paper
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Accelerating LLM Inference by Enabling Intermediate Layer Decoding
Neeraj Varshney, Agneet Chatterjee, Mihir Parmar, Chitta Baral
NAACL 2024 (Findings)
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This website's source code is borrowed from Jon Barron.
Last Updated: August 2026
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