Talk on MLLM

[Talk on MLLM @robot_llm]

@HonpengZ

[Talk on MLLM @robot_llm]

【20 July 2024】 MLLM Talk:
🍀 OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning
📷Tairan He @TairanHe99 | Carnegie Mellon University https://t.co/A38WLBScNA
📷More https://t.co/sJFxAqCJkP

#LLM #Robot

[Talk on MLLM @robot_llm]

@TairanHe99 @chuang_yu_ @ppsunrise @QianqianXie727 @huang_guanyu @Siyang_Song_05 @Garyxiehd @tangjiabin7 @Jiachen_Gu

[Talk on MLLM @robot_llm]

@TairanHe99 @chuang_yu_ @ppsunrise @QianqianXie727 @huang_guanyu @Siyang_Song_05 @Garyxiehd @tangjiabin7 @weizhe_lin_flmr

[Talk on MLLM @robot_llm]

【7 July 2024】 MLLM Talk:
🍀 MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
📷Xiangru Tang @XiangruTang | Yale University https://t.co/RTBjiQBLRa
📷https://t.co/sJFxAqCJkP

#AGI #LLM

[Zhutian (Skye) Yang @ZhutianYang_]

#ICRA2024 How are vision language models changing our approach to navigation and manipulation? Come find out and hang out! https://t.co/a9aaMklJN9

[Kailai Yang @KailaiYang]

Come check out our Poster at The ACM Web Conference 2024. #TheWebConf24 - via #Whova event app

[WizardLM @WizardLM_AI]

🫡 We are sorry for that.

It’s been a while since we’ve released a model months ago😅, so we’re unfamiliar with the new release process now: We accidentally missed an item required in the model release process - toxicity testing.

We are currently completing this test quickly and then will re-release our model as soon as possible. 🏇

❤️Do not worry, thanks for your kindly caring and understanding.

[Talk on MLLM @robot_llm]

【24 April 2024】 MLLM Talk:
🍀 In-context Learning of Large Language Model
🏂Ruiqi Zhang | University of California, Berkeley https://t.co/580JhdFFtz
🧐 https://t.co/sJFxAqCJkP

[Spencer Frei @sfrei_]

Super excited about my new paper on in-context learning of linear models with transformers: https://t.co/zmYCUxoM1Q
The lead author on this work is Ruiqi Zhang, a super talented first-year PhD student in Statistics at UC Berkeley, and this is joint work with Peter Bartlett.

[Talk on MLLM @robot_llm]

【6th April 2024】 MLLM Talk:
🍀 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

🏂Ming Jin | Monash University https://t.co/mN9JrSesYa

🧐 https://t.co/sJFxAqCJkP

[Talk on MLLM @robot_llm]

Coming MLLM Talk:
🍀 Large Language Models as Commonsense Knowledge for Large-Scale Task Planning

🏂 Zirui Zhao | National University of Singapore https://t.co/2skKCbgAoH

⌚️ 7PM (GMT+8) @Singapore | 11AM (GMT+0) @London| 30th March 2024

🧐 https://t.co/sJFxAqCJkP

[Xi Wang @wangxieric]

Just present our paper @ecir2024. As I mentioned at the end of the talk, I am looking for PhD students who have a shared interest with me on the topic of Personalisation in Conversational AI to join @SheffieldNLP. Feel free to get in touch with the details.

[Santiago Ortiz @moebio]

Interactive visualization of chatgpt completion probabilities, I ask it to to complete the prompt "When " hundreds of times.

[Talk on MLLM @robot_llm]

by @tangjiabin7

[Talk on MLLM @robot_llm]

Coming MLLM Talk:
🍀 Graph Language Models
📷 Jiabin Tang | Data Intelligence Lab, The University of Hong Kong
📷 12PM(GMT+0) Noon @ London Time | 24th March 2024

🧐 https://t.co/PiSX9Xrq9H

#LLM #ChatGPT #mllmtalk

[Ziniu Hu @acbuller]

Interested in LLM + Tool-Use, via Tree-Search?

This afternoon in #NeurIPS2023, #215, I'll present "AVIS: Autonomous Visual Information Seeking with Large Language Model Agent" (https://t.co/g26i5Wv12l)

Feel free to drop by and chat.

[Lili @lchen915]

How can robots perform a wide range of skills? At #CoRL2023, we presented PlayFusion – a language-conditioned discrete diffusion model capable of performing many different tasks!

🌐https://t.co/WOR0NaQOUW

1/n

[Zhiting Hu @ZhitingHu]

🔥#NeurIPS2023 Tutorial🔥

Language Models meet World Models

@tianminshu & I are excited to give tutorial on machine reasoning by connecting LLMs🗣️ world models🌎 agent models🤖

w/ amazing panelists @jiajunwu_cs @du_yilun Ishita Dasgupta,Noah Goodman

https://t.co/KJFyEd6FQz

[Zhutian (Skye) Yang @ZhutianYang_]

Our new RSS paper shows that neural networks can help robots plan in a kitchen faster. Our PIGINet plan feasibility classifier uses Transformer and pre-trained CLIP model to speed up task and motion planning in geometrically complex environments. @NVIDIAAIDEV @MIT_CSAIL @RSS2023