Zijie Li @ZijieLi00
PhD Mechanical Engineering@CMU, AIGC researcher @ ByteDanceSeed, AI for simulation, generative modeling https://t.co/b329xDNjfd Pittsburgh, PA Joined May 2023-
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If you're at #ICLR 2025 in Singapore, please check out our posters 🤗 I'm sure it's going to be a great conference! Have fun everyone...
The full PBDL book is available in a single PDF now arxiv.org/pdf/2109.05237, and has grown to 451 pages 😳 Enjoy all the new highlights on generative models, simulation-based constraints and long term stability with diffusion & flow matching 😁
文字 P 图哪家强？字节 SeedEdit 与 Gemini 2.0对比测试 最近谷歌 Gemini 2 Flash 的原生多模态图像修改和编辑能力很火，但很多人说用不了 刚好字节的 SeedEdit 也支持这些功能，最近好像也有升级 顺便帮大家测试一下，下面是详细测试👇
🚨Announcing our #ICLR2025 Oral! 🔥Diffusion LMs are on the rise for parallel text generation! But unlike autoregressive LMs, they struggle with quality, fixed-length constraints & lack of KV caching. 🚀Introducing Block Diffusion—combining autoregressive and diffusion models…
Block Diffusion Interpolating Between Autoregressive and Diffusion Language Models
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to…
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to…
Excited to share that I’ve been working on scaling up diffusion language models at Inception. A new generation of LLMs with unprecedented capabilities is coming!
Excited to share that I’ve been working on scaling up diffusion language models at Inception. A new generation of LLMs with unprecedented capabilities is coming!
This is really insane. They took all the bet and scaled up discrete diffusion model to llama-7B scale. IIRC nobody dared to do this at this scale but these madlads done it. They even fine-tuned it to be a dialogue model. This is really frontier-level shit that is genuinely new…
Happy to see that our work, LLM-SR, has been accepted to #ICLR 2025! 🇸🇬 If you’re interested in learning how LLMs can be used for scientific equation discovery, check this out 👇🏻
Happy to see that our work, LLM-SR, has been accepted to #ICLR 2025! 🇸🇬 If you’re interested in learning how LLMs can be used for scientific equation discovery, check this out 👇🏻
Introducing NeuralOperator 1.0: a Python library that aims at democratizing neural operators for scientific applications by providing all the tools for learning neural operators in PyTorch : state-of-the-art models, built-in trainers for quick starting and modular neural operator…
Excited to present our #NeurIPS2024 paper: "Simple and Effective Masked Diffusion Language Models" on Thurs at 11:30 a.m. in Hall A-C (#2505) 🔥 Our method, MDLM, almost surpasses AR models in text generation 📕 arxiv.org/abs/2406.07524 💻 github.com/kuleshov-group… 📒…
Here's one to read on your flight to #NeurIPS2024! A flow-matching transformer model in function space! This model has all the advantages of neural fields: resolution-free generation and domain-agnostic architecture, while obtaining strong results on ImageNet-256 and Objaverse!
Here's one to read on your flight to #NeurIPS2024! A flow-matching transformer model in function space! This model has all the advantages of neural fields: resolution-free generation and domain-agnostic architecture, while obtaining strong results on ImageNet-256 and Objaverse!
A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.
I'm excited to share our APEBench paper arxiv.org/abs/2411.00180 and code github.com/tum-pbs/apeben…, to be presented at #NeurIPS. Congratulations Felix and Simon 😀 👍 APEBench features a lightning-fast ⚡️ fully differentiable spectral solver with a huge range of different PDEs
Super hyped to share NeuralDEM -- the first real-time simulation of industrial particulate flows. NeuralDEM replaces Discrete Element Method (DEM) routines and coupled (CFD-DEM) multiphysics simulations. 🧵 📜: arxiv.org/abs/2411.09678 🖥️: nx-ai.github.io/NeuralDEM/
Our new paper in @NatMachIntell tells a story about how, and why, ML methods for solving PDEs do not work as well as advertised. We find that two reproducibility issues are widespread. As a result, we conclude that ML-for-PDE solving has reached overly optimistic conclusions.
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43K Followers 3K Following We're in a race. It's not USA vs China but humans and AGIs vs ape power centralization. @deepseek_ai stan #1, 2023–Deep Time «C’est la guerre.» ®1
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batuhan the fal guy @isidentical
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