Chen Tang

Assistant Professor in New Mobility @UCLA | CS Postdoc @UTAustin | ME PhD @UCBerkeley

[Chen Tang @ChenTangMark]

I’m excited to share that I will be joining the CEE Department at @UCLA as an Assistant Professor in New Mobility this Fall! I am recruiting Ph.D. students for Fall25/Spring 26/Fall26. There are also opportunities for master’s, undergrads, and postdocs.

[Chen Tang @ChenTangMark]

Excited to share our new findings on continual RL for VLA models. Surprisingly simple methods can already enable strong performance. Great work led by @JiahengHu1 and @jayjshim

[Jiaheng Hu @JiahengHu1]

VLA models are capable generalists. But can they continually self-improve?

Such Continual Reinforcement Learning (CRL) problems are traditionally considered very challenging.

Surprisingly, we found that with the right setup, the simplest CRL recipe can work really well!

https://t.co/7DmlhAqX9L

[Jiaheng Hu @JiahengHu1]

VLA models are capable generalists. But can they continually self-improve?

Such Continual Reinforcement Learning (CRL) problems are traditionally considered very challenging.

Surprisingly, we found that with the right setup, the simplest CRL recipe can work really well!

https://t.co/7DmlhAqX9L

[Chen Tang @ChenTangMark]

@cuijiaxun I am so sorry to hear that…

[Chen Tang @ChenTangMark]

How can we align a policy with human preferences efficiently? MEReQ tackles this by inferring residual rewards that capture discrepancies from human experts and adapting via residual Q-learning (https://t.co/C5DJi0P0dJ). Check it out at CoRL along with @Yuxin’s other work, ReLIC!

[Yuxin Chen @ThomasYuxinChen]

Two papers to be presented at #CoRL2025!

ReLIC: Loco-manipulation with interlimb coordination
🎙️ Oral 1 (Manipulation I)-7, Poster 1-56
🔗 https://t.co/eSCKo0NEw3

MEReQ: Sample-efficient alignment from human intervention
🎙️ Spotlight 2-44, Poster 1-36
🔗 https://t.co/JlnK4gAF8G

[Chen Tang @ChenTangMark]

It’s crucial for robots to navigate in line with user preferences among crowds. Excited to share ComposableNav that allows composable instruction-following navigation in dynamic environments. If you’re at CoRL, check it out—@michaelmunje will present it alongside SocialNav-SUB!

[Zichao @ZichaoHu99]

How can robots follow complex instructions in dynamic environments?

🤖 Meet ComposableNav — a diffusion-based planner that enables robots to generate novel navigation behaviors that satisfy diverse instruction specifications on the fly — no retraining needed.

📄 Just accepted to CoRL 2025
🔗 Project: https://t.co/FX3O0ZYYyD

A Thread (1/8)

[Chen Tang @ChenTangMark]

Check out our new benchmark for testing whether VLMs can truly understand social navigation scenes and align with human reasoning. We hope the community finds it useful for advancing foundation models in social navigation. Catch @michaelmunje at CoRL 2025 to learn more!

[Michael Munje @michaelmunje]

[1/8] New social navigation paper + benchmark: SocialNav-SUB 🚶🤖 Recent work puts VLMs on robots for navigation, but can they really interpret scenes and extract key details for social navigation? 🔎 https://t.co/2rlcIQpf6h

[Chenfeng_X @Chenfeng_X]

📢 Excited to sharing a little late update (before it is no longer news): I’ll be joining @UTAustin @UTCompSci as an Assistant Professor! I'm recruiting PhD students from @UTCompSci in the Fall 2025 cycle and also looking for RAs/interns! More info see https://t.co/JPDhVplhJX

[Yoonchang Sung @yoonchangsung]

I’m hiring multiple PhD students and one postdoc at NTU Singapore, starting in Spring or Fall 2026, to push the frontiers of robot planning, learning, and embodied AI.

Details are available here: https://t.co/WDCOPVW8kJ

Thank you for your support in sharing this opportunity!
#PhDOpportunity #Robotics #NTUsg

[Yuxin Chen @ThomasYuxinChen]

💡Can we let an arm-mounted quadrupedal robot to perform task with both arms and legs?

Introducing ReLIC: Reinforcement Learning for Interlimb Coordination for versatile loco-manipulation in unstructured environments. [1/6]

https://t.co/cOyPC5ZOvp

[Jiaxun Cui 🐿️ @cuijiaxun]

[1/n] Can LLM Agents learn to communicate and coordinate in natural language in driving scenarios 🚗 through self-play interactions? Our recent research shows the potential for such learning; interestingly, there is evidence that they develop concise protocols for collaboration! A distilled version of the agents’ model could generalize to multiple scenarios, communicate at 250 bytes per message, and make decisions within 500 ms while maintaining the original (large) model’s performance.
💬Natural Language Communication among Autonomous Agents
✨Multi-agent Gymnasium for Policy Learning
👀Partial Observation and Negotiation Tasks
More videos & analysis
project page: https://t.co/KYrgvj6Waj
arXiv: https://t.co/Mq608FbslP
with @ChenTangMark, Jarrett Holtz, Janice Nguyen, @aleallievi, @HangQiu, @PeterStone_TX

open to discussion & collaboration!
@utlarg @texas_robotics
#LLM #multiagent

[Association for Computing Machinery @TheOfficialACM]

🙌 Meet the 2024 ACM Technical Awards Recipients!
We’re proud to honor this year’s innovators in autonomous systems, cryptography, and software for parallel computers:

🏆 Peter Stone – ACM-AAAI Allen Newell Award
For significant contributions to the theory and practice of artificial intelligence (AI). @UTAustin @SonyAI_global
🔗 https://t.co/U4vpUvBgyX

[Chen Tang @ChenTangMark]

@JiahengHu1 Thanks Jeff!

[Chen Tang @ChenTangMark]

I am deeply grateful to my advisors, mentors, friends, and family for their support throughout my job search! Looking forward to this new chapter at UCLA!

[Chen Tang @ChenTangMark]

I’m excited to share that I will be joining the CEE Department at @UCLA as an Assistant Professor in New Mobility this Fall! I am recruiting Ph.D. students for Fall25/Spring 26/Fall26. There are also opportunities for master’s, undergrads, and postdocs.

[Chen Tang @ChenTangMark]

Check out my website for more details about opportunities for prospective students: https://t.co/mCWLq2AnhZ. Feel free to share this with anyone who might be interested!

[Chen Tang @ChenTangMark]

Organizers: @ChenTangMark, @yifengzhu_ut, Yue Meng, @siddkaramcheti, @andreea7b

Advisory Board: @yukez, @PeterStone_TX

[Chen Tang @ChenTangMark]

Foundation models like LLMs and VLMs have transformed AI and our digital interactions, but what challenges arise when these models operate in physical, human-centric environments? Join us at the human-centered robot learning workshop at #ICRA2025 to explore these questions!

[Chen Tang @ChenTangMark]

We are also inviting contributions! If your research aligns with our workshop themes, we’d love to see your work presented. Looking forward to seeing you in Atlanta soon!

Workshop Website: https://t.co/WDOMGmYbcx