Title: Anchored Discrete Diffusion Models for Language Generation and Image Editing
Time & Venue: December 20, 2025 09:00 – 10:00 hrs IST; Biological Science Auditorium (Department of Biological Sciences, IISc)
Abstract:
In this talk, we discuss discrete diffusion models that offer a unified framework for jointly modeling categorical data such as text and images. We first discuss a new model we have developed for language generation called the Anchored Diffusion Language Model (ADLM). ADLM is grounded in a novel two-stage framework that first predicts distributions over important tokens via an anchor network (e.g., key words or low-frequency words that anchor a sentence), and then predicts the likelihoods of missing tokens conditioned on the anchored predictions. ADLM significantly improves test perplexity on LM1B and OpenWebText, achieving up to 25.4% gains over prior DLMs, and narrows the gap with strong AR baselines. It also achieves state-of-the-art performance in zero-shot generalization across seven benchmarks and surpasses AR models in MAUVE score, which marks the first time a DLM generates better human-like text than an AR model.
We next discuss posterior sampling for images using pretrained discrete diffusion foundation models, aiming to recover images from noisy measurements without retraining task-specific models. We introduce
Anchored Posterior Sampling (APS) for masked diffusion foundation models, built on two key innovations—quantized expectation for gradient-like guidance in discrete embedding space, and anchored remasking for adaptive decoding. Our approach achieves state-of-the-art performance, and demonstrates training-free stylization and text-guided editing using our sampler. (Based on joint work with Litu Rout, Constantine Caramanis, Andreas Lugmayr, Yasamin Jafarian, Srivatsan Varadharajan, Ira Kemelmacher-Shlizerman at UT Austin and Google; see project pages:
https://anchored-diffusion-llm.github.io/ ,
https://anchored-discrete-ps.github.io/ )
Speaker Bio:
Sanjay Shakkottai received his Ph.D. from the ECE Department at the University of Illinois at Urbana-Champaign in 2002. He is with The University of Texas at Austin, where he is a Professor in the ECE and CS Departments, and holds the Cockrell Family Chair in Engineering #15. He is also the Director of the Center for Generative AI, a campus-wide computing cluster at UT Austin. He received the NSF CAREER award in 2004 and was elected as an IEEE Fellow in 2014. He was a co-recipient of the IEEE Communications Society William R. Bennett Prize in 2021. He has served as the Editor in Chief of IEEE/ACM Transactions on Networking. His current research interests are in diffusion models and Generative AI, with applications in language models, image editing, and decision-making in wireless networks.
