https://nitter.cf/t.co/Q2OjzQmHnm
Cambridge, England
Joined November 2021
- Tweets65
- Following110
- Followers46
- Likes30
【20 July 2024】 MLLM Talk:
🍀 OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning
📷Tairan He @TairanHe99 | Carnegie Mellon University tairanhe.com/
📷More mllm-ai.com
#LLM #Robot
【7 July 2024】 MLLM Talk:
🍀 MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
📷Xiangru Tang @XiangruTang | Yale University xiangrutang.github.io/
📷mllm-ai.com
#AGI #LLM
Talk on MLLM retweeted
#ICRA2024 How are vision language models changing our approach to navigation and manipulation? Come find out and hang out! vlmnm-workshop.github.io/
Talk on MLLM retweeted
Come check out our Poster at The ACM Web Conference 2024. #TheWebConf24 - via #Whova event app
Talk on MLLM retweeted
🫡 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.
🔥Today we are announcing WizardLM-2, our next generation state-of-the-art LLM.
New family includes three cutting-edge models: WizardLM-2 8x22B, 70B, and 7B - demonstrates highly competitive performance compared to leading proprietary LLMs.
📙Release Blog: wizardlm.github.io/WizardLM2
✅Model Weights: huggingface.co/collections/m…
ALT MT-Bench
【24 April 2024】 MLLM Talk:
🍀 In-context Learning of Large Language Model
🏂Ruiqi Zhang | University of California, Berkeley rqzhangberkeley.github.io/
🧐 mllm-ai.com
Talk on MLLM retweeted
Super excited about my new paper on in-context learning of linear models with transformers: arxiv.org/abs/2306.09927
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.
【6th April 2024】 MLLM Talk:
🍀 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
🏂Ming Jin | Monash University mingjin.dev/
🧐 mllm-ai.com
Coming MLLM Talk:
🍀 Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
🏂 Zirui Zhao | National University of Singapore 1989ryan.github.io
⌚️ 7PM (GMT+8) @Singapore | 11AM (GMT+0) @London| 30th March 2024
🧐 mllm-ai.com
Talk on MLLM retweeted
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.
Talk on MLLM retweeted
Interactive visualization of chatgpt completion probabilities, I ask it to to complete the prompt "When " hundreds of times.
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
🧐 mllm-ai.com
#LLM #ChatGPT #mllmtalk
Talk on MLLM retweeted
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" (blog.research.google/2023/08…)
Feel free to drop by and chat.
Talk on MLLM retweeted
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!
🌐play-fusion.github.io
1/n
Talk on MLLM retweeted
🔥#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
sites.google.com/view/neurip…
Talk on MLLM retweeted
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