Maitreya Patel

Ph.D. Student, School of Computing & AI, Arizona State University.


I am a Ph.D. student at Arizona State University (ASU). I am working alongside Yezhou Yang and Chitta Baral. I closely collaborate with Tejas Gokhale and Changhoon Kim.

My focus lies in the domain of Robust and Reliability for Vision-Language. Currently, I specialize in computer vision, specifically generative and diffusion models, concept algebra, model attribution, and few-shot learning. I firmly believe that advancing Counterfactual/Causal Reasoning is essential for enhancing the reliability of machine learning systems in the long run.

Aside from academics, I enjoy working on intriguing open-source projects. Recently, I have dedicated my free time to developing reliability-checklist (v0.1.0 released) and AInos (under review for product market fit).


May 28, 2024 🎬 Started intern at Adobe as Research Intern for Summer 2024.
Feb 26, 2024 Two papers (ECLIPSE and WOUAF) accepted @ CVPR'24. :fire: :fire:
Feb 24, 2024 Presented ConceptBed @ AAAI'24. :sparkles: :smile:
Feb 7, 2024 We release λ-ECLIPSE, the resource-effecient Multi-Subject Text-to-Image Model. :sparkles:
Jan 26, 2024 Organizing semester long seminar series on Frontier Topics in GenAI Seminar.

Selected Publications

  1. ECLIPSE:A Resource-Efficient Text-to-Image Prior for Image Generations
    Maitreya Patel Changhoon Kim, Sheng Cheng, Chitta Baral, and Yezhou Yang

    In CVPR – 2024

  2. WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models
    Changhoon Kim*Kyle Min* Maitreya Patel , Sheng Cheng, and Yezhou Yang
    Media Coverages:  AK  

    In CVPR – 2024

  3. λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Space
    Maitreya Patel , Sangmin Jung, Chitta Baral, and Yezhou Yang
    Media Coverages:  AK   , MarkTechPost

    In ArXiv – 2024

  4. ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion Models
    Maitreya Patel Tejas GokhaleChitta Baral, and Yezhou Yang

    In AAAI’24 | Diffusion Workshop at NeurIPS – 2023

  5. CRIPP-VQA: Counterfactual Reasoning about Implicit Physical Properties via Video Question Answering
    Maitreya Patel Tejas GokhaleChitta Baral, and Yezhou Yang

    In EMNLP, Main Conference – 2022

  6. Benchmarking generalization via in-context instructions on 1,600+ language tasks
    Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, and  others

    In EMNLP, Main Conference – 2022

  7. MSpeC-Net: Multi-Domain Speech Conversion Network
    Harshit Malaviya, Jui Shah,  Maitreya Patel , Jalansh Munshi, and Hemant A Patil

    In 45th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020

  8. CinC-GAN for Effective F0 prediction for Whisper-to-Normal Speech Conversion
    Maitreya Patel , Mirali Purohit, Jui Shah, and Hemant A Patil

    In 28th European Signal Processing Conference (EUSIPCO) 2020

  9. Weak Speech Supervision: A case study of Dysarthria Severity Classification
    Mirali Purohit, Mihir Parmar Maitreya Patel , Harshit Malaviya, and Hemant A Patil

    In 28th European Signal Processing Conference (EUSIPCO) 2020

  10. Novel adaptive generative adversarial network for voice conversion
    Maitreya Patel Mihir Parmar, Savan Doshi, Nirmesh J Shah, and Hemant A Patil

    In 11th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 2019

  11. Effectiveness of cross-domain architectures for whisper-to-normal speech conversion
    Mihir Parmar, Savan Doshi, Nirmesh J Shah,  Maitreya Patel , and Hemant A Patil

    In 27th European Signal Processing Conference (EUSIPCO) 2019