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David-cripto/README.md

David Li

From slow samplers to few-step generators.

Website Google Scholar LinkedIn X LiSearch Telegram YouTube Email

About me

I work on fast generative modeling: distilling diffusion and matching-model teachers into compact students that sample in a few steps.

Currently, I am a first-year PhD student at MBZUAI, supervised by Eric Moulines, Maxim Panov, and Alexander Korotin.

Selected highlights

Project Venue Focus Links
IDLM ICML 2026 Few-step diffusion language generation Project / Paper / Code
RealUID ICLR 2026 Oral Real-data inverse distillation Paper / Code
IBMD ICML 2025 Fast bridge-model generation Paper / Code

LiSearch

I run LiSearch, a small channel for reading, explaining, and discussing generative model papers.

LiSearch Telegram LiSearch YouTube

Connect

For the full publication list, see my research page. For a conversation, reach me by email, LinkedIn, or X.

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  1. IDLM IDLM Public

    (ICML 2026) IDLM: Inverse-distilled Diffusion Language Models

    Python 13

  2. RealUID RealUID Public

    (ICLR 2026 Oral 🔥) Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)

    Python 17 1

  3. gregkseno/ipmf gregkseno/ipmf Public

    [ICLR 2026] Diffusion & Adversarial Schrödinger Bridges via Iterative Proportional Markovian Fitting

    Python 7

  4. RDAS RDAS Public

    Reduction of Dimensionality through Active Subspaces approach

    Jupyter Notebook 4 1

  5. FSDDPM FSDDPM Public

    Fast samplin of DDPM models

    Jupyter Notebook 1

  6. Tower-defense-in-python Tower-defense-in-python Public