Robotic Research @ NVIDIA GEAR PhD @ NTU
Sicong Leng冷思聪
Towards generalist intelligence for the physical world.
I'm a fourth-year PhD student at NTU, advised by Prof. Shijian Lu, and work on robotics at NVIDIA GEAR.
I study how machines can learn from diverse experience, reason beyond what they have seen, and turn understanding into useful action.
01 / Research
Selected work
Scaling how machines learn, reason, and act.
RynnBrain 1.1
Towards robots that generalize beyond a single task.
Connecting perception, spatial reasoning, and action in a shared foundation for learning across tasks and embodiments.
More selected work
Publication archivearXiv 2026
Vesta: A Generalist Embodied Reasoning Model
CVPR 2026
MMR1: Enhancing Multimodal Reasoning with Variance-Aware Sampling and Open Resources
ArXiv 2025
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
ArXiv 2024
VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
CVPR 2024 · Highlight
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
For the full publication list, visit Google Scholar ↗.
02 / Updates
Recently
New work and open releases.
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Introducing Flora: open models for timestamped action captions and reward signals, powering the robotics data engine for GR00T.
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RynnBrain 1.1 is open source, with stronger embodied understanding, contact-point prediction, and native 3D grounding.
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Vesta brings localization, navigation, reasoning, and planning into one embodied generalist.
More updates
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New survey out: World Model for Robot Learning: A Comprehensive Survey — a policy-centric look at world models for robot learning.
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New survey out: Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling — a roadmap from atomic mapping to agentic world modeling.
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RynnBrain is released — open embodied foundation models for robotics.
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RynnVLA-001 accepted by ICRA 2026.
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MMR1 is out — variance-aware sampling for multimodal reasoning, with open-sourced code, data, and model.
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CMM and Better MoE accepted by NeurIPS 2025 — Better MoE as oral.
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RynnVLA-001 is released — a vision-language-action model pretrained on human demonstrations for robot manipulation.
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Inf-CLIP received the CVPR 2025 Highlight.
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MMR1 has been released — initial code drop for our multimodal reasoning research.
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VideoLLaMA 3 has been released.
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Inf-CLIP has been released! Project.
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CMM has been released! Project.
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1 paper accepted by NeurIPS 2024!
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VideoLLaMA 2 has been released! Paper & code.
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VCD received the CVPR 2024 Highlight.
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3 papers accepted by CVPR 2024!
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VCD has been released! Paper & code.
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Presented our work at the Nvidia Internal Technical Sharing.
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Presented our work at the AAAI 2023 Summer Symposium Series.
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Tell2Design received the Area Chair Award and Best Paper Nomination at ACL 2023!
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Tell2Design accepted by ACL 2023 as a long oral paper.
03 / Background
Along the way
May 2026 – Present
Aug 2023 – May 2026
Sep 2021 – Aug 2023
StatNLP Lab, SUTD
Research Officer
NLP and multimodal learning, including language-guided floor plan generation with Tell2Design.
With Prof. Lu Wei
“We were born too late to explore the earth and too early to explore the stars. We were born just in time to solve robotics. I'm on a mission to make Physical AI a reality, one motor at a time.”
Let's connect.
Away from research: badminton, singing, and games.
Lengsicong@gmail.com