Lingpeng Kong
@ikekong
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Assistant Professor @ The University of Hong Kong, Previously Research Scientist @ DeepMind
Hong Kong
Joined February 2010
Smarter TTS by Xueliang! See everyone in this year NeurIPS!
🚀 Thrilled to share our #NeurIPS2025 paper DynaAct: Large Language Model Reasoning with Dynamic Action Spaces A new test-time scaling view — optimizing the action space itself, while providing a general MCTS acceleration framework for reasoning. 💻 https://t.co/FFWIDBcbCV
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This is super cool. I strongly believe that the flexibility of dLLMs during generation will enable new features for agent use.
Diffusion LLM + Agents are 🔥 This is @_inception_ai's Diffusion LLM with @huggingface SmolAgents: - Planning tool use - Executing 20 web searches and parsing results - Synthesizing the data All in 3.5 seconds. With 10 searches it took only 1.6 seconds. Source on GitHub below.
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We will have a guest talk from Cai Zhou. He is a second-year PhD in MIT EECS. "Continuous modeling in diffusion language models: HDLM and CCDD ". All are welcome to join via the following link. https://t.co/ZlLDO5pKRH
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DeepSeek-OCR: Exploring the boundaries of visual-text compression. Ambitious! They might use 10X (near-lossless) compressed vision tokens to replace the KV cache of dialog histories. https://t.co/gxjLBrkCWW
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The full Dream-Coder pipeline is now open-sourced—covering data prep, training, and evaluation. Check it out!
github.com
Contribute to DreamLM/Dream-Coder development by creating an account on GitHub.
🚀 Thrilled to announce Dream-Coder 7B — the most powerful open diffusion code LLM to date.
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Saw the paper like a month ago. Now with the demo it only gets cooler :p
Introducing Generative Interfaces - a new paradigm beyond chatbots. We generate interfaces on the fly to better facilitate LLM interaction, so no more passive reading of long text blocks. Adaptive and Interactive: creates the form that best adapts to your goals and needs!
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🌟 Thrilled to share our paper, "TreeSynth," has been accepted for a Spotlight presentation at #NeurIPS2025! 🤔 Struggling with repetition & space collapse in data synthesis? Our work introduces 🌳TreeSynth, a novel framework using tree-guided partitioning to generate
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Jinjie Ni @NiJinjie from NUS will be giving a talk titled "Diffusion Language Models are Super Data Learners" at Friday Aug 22 11am HKT. link to talk: https://t.co/WxTUSok1in
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🚀 MiMo‑VL 2508 is live! Same size, much smarter. We’ve upgraded performance, thinking control, and overall user experience. 📈 Benchmark gains across image + video: MMMU 70.6, VideoMME 70.8. Consistent improvements across the board. 🤖 Thinking Control: toggle reasoning with
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Xinyu Yang from CMU will be giving a talk titled "Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation" at Friday July 25 11am HKT (Thursday July 24 8pm PDT). Link to talk: https://t.co/Cdn9TGqWQ2
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📢 Update: Announcing Dream's next-phase development. - Dream-Coder 7B: A fully open diffusion LLM for code delivering strong performance, trained exclusively on public data. - DreamOn: targeting the variable-length generation problem in dLLM!
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🚀 Thrilled to announce Dream-Coder 7B — the most powerful open diffusion code LLM to date.
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We present DreamOn: a simple yet effective method for variable-length generation in diffusion language models. Our approach boosts code infilling performance significantly and even catches up with oracle results.
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Please check out our blogs here. Dream-Coder 7B: https://t.co/d2zHHwhpg2 DreamOn:
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What happend after Dream 7B? First, Dream-Coder 7B: A fully open diffusion LLM for code delivering strong performance, trained exclusively on public data. Plus, DreamOn cracks the variable-length generation problem! It enables code infilling that goes beyond a fixed canvas.
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🤖Can diffusion models write code competitively? Excited to share our latest 7B coding diffusion LLM!!💻 With DiffuCoder, we explore how they decode, why temperature🔥 matters, and how to improve them via coupled-GRPO that speaks diffusion!!📈 Code: https://t.co/sWsb8a49HL 🧵
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Fun especially considering this is a shiba :)
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Huge milestone from the team! A blazing-fast diffusion LLM built for chat, delivering real-time performance at commercial scale. If you liked Mercury Coder for code, you'll love this for conversation.
We’re excited to launch Mercury, the first commercial-scale diffusion LLM tailored for chat applications! Ultra-fast and efficient, Mercury brings real-time responsiveness to conversations, just like Mercury Coder did for code.
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Thanks for sharing our work!!!🙏Code release is in progress😺
DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation Apple introduces DiffuCoder, a 7B diffusion LLM trained on 130B tokens of code authors also propose a diffusion-native RL training framework, coupled-GRPO Decoding of dLLMs differ from
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MiMo-VL technical report, models, and evaluation suite are out! 🤗 Models: https://t.co/7NhlMdszpD (or RL) Report: https://t.co/j78x15eomk Evaluation Suite: https://t.co/FcQJBIUMkk Looking back, it's incredible that we delivered such compact yet powerful vision-language
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