Heng Dong
@drdhxi
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Ph.D. Student at Tsinghua University
Joined May 2020
💥Excited to share our paper “AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time” at #EMNLP2025 🚀 this Friday, Nov. 7, during Gather Session 4. Come say hi virtually!👋 📄Paper: https://t.co/CksN8hEuoF 🪩Website & Code: https://t.co/AwMLAQFvtz
#AI #LLMs #Reasoning
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Huge thanks for sharing our work @_akhaliq! AlphaOne deep dive & code release coming soon 🚀
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🤔Tired of agents stumbling in the dark? Making the right decision is tough without complete information. 🔎Diffusion models are here to infer global information from local observations! ✈️arxiv: https://t.co/svYGLs02Cb
@MilindTambe_AI, @drdhxi, @Yanchen_Jiang, David Parkes.
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Present our novel work “Leveraging Hyperbolic Embeddings for Coarse-Fine Robot Design” in #ICLR2024 in #Vienna. Welcome to visit our website https://t.co/d5nzA2U8mz if you are interested. Also many thanks to my excellent co-author @jyzhang1208. Without her, nothing could be done.
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Our work in #ICML2023: Symmetry-Aware Robot Design with Structured Subgroups. https://t.co/JtUsDvALP3
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Very excited to share our #NeurIPS2022 paper: Low-Rank Modular Reinforcement Learning via Muscle Synergy. Motivated by human muscle synergy, we designed an efficient framework that achieves low-rank control over high DoF robots. Project:
sites.google.com
Abstract Modular Reinforcement Learning (RL) decentralizes the control of multi-joint robots by learning policies for each actuator. Previous work on modular RL has proven its ability to control...
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