Yuxiang (Jimmy) Wu @YuxiangJWu
Co-founder @WecoAI | UCL PhD | Natural Language Processing | Machine Learning | formerly intern @allen_ai @MetaAI yuxiang.me Joined October 2014-
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Here you go, no more waitlisting and just run it locally! Local version of AIDE currently serves as a powerful tool for data scientists and machine learning engineers to explore draft designs.
Here you go, no more waitlisting and just run it locally! Local version of AIDE currently serves as a powerful tool for data scientists and machine learning engineers to explore draft designs.
Great works from @zhengyaojiang, @YuxiangJWu and the @WecoAI team! Maybe I can delegate all my request calling pandas for data processing to Weco's AIDE 😀
Great works from @zhengyaojiang, @YuxiangJWu and the @WecoAI team! Maybe I can delegate all my request calling pandas for data processing to Weco's AIDE 😀
Watching AIDE autonomously tackle ML problems by designing, implementing, and iterating on code, conducting experiments, and evaluating results has been nothing short of fascinating. Can't wait to see how it will revolutionize DS and ML workflows, enabling a broader range of…
Watching AIDE autonomously tackle ML problems by designing, implementing, and iterating on code, conducting experiments, and evaluating results has been nothing short of fascinating. Can't wait to see how it will revolutionize DS and ML workflows, enabling a broader range of… https://t.co/ww4OetWzGf
We're excited to announce AIDE has become the first human-level AI agent for data science! AIDE outperforms half of human data scientists on a wide range of Kaggle competitions, surpassing conventional AutoML, LangChain agents, and ChatGPT with human assistance. 🏆
The concept of LLM-driven software engineers is intriguing, but in most cases, they still fall short of human engineers without human oversight. Our AI agent has changed the game by outperforming half of the data scientists in Kaggle competitions with zero human intervention!
The concept of LLM-driven software engineers is intriguing, but in most cases, they still fall short of human engineers without human oversight. Our AI agent has changed the game by outperforming half of the data scientists in Kaggle competitions with zero human intervention!
We are working on an open leaderboard for measuring hallucinations in LLMs! 🚀🚀🚀 Read more about it here: huggingface.co/blog/leaderboa… Leaderboard address (and discussion forum, if you'd like to provide feedback or help 🙂): huggingface.co/spaces/halluci…
We are working on an open leaderboard for measuring hallucinations in LLMs! 🚀🚀🚀 Read more about it here: huggingface.co/blog/leaderboa… Leaderboard address (and discussion forum, if you'd like to provide feedback or help 🙂): huggingface.co/spaces/halluci… https://t.co/9HPmqMseKa
Today we’re announcing Weco AI and our first product, AIDE: your AI agent for Machine Learning. Simply describe your task in natural language, and AIDE will search the design space to deliver source code and a report for you. Join the waitlist now at weco.ai (1/3)
Extremely excited to announce new work (w/ @MinqiJiang) on learning RL policies and world models purely from action-free videos. 🌶️🌶️ LAPO learns a latent representation for actions from observation alone and then derives a policy from it. Paper: arxiv.org/abs/2312.10812
🚀Excited to share this work by @zodiacJRH and team on enhancing LLM robustness using Natural Language Explanations (NLEs)! When prompted with few-shot human-written explanations, ChatGPT can generate better NLEs for improving robustness of LLM. arxiv.org/abs/2311.07556
🚀Excited to share this work by @zodiacJRH and team on enhancing LLM robustness using Natural Language Explanations (NLEs)! When prompted with few-shot human-written explanations, ChatGPT can generate better NLEs for improving robustness of LLM. arxiv.org/abs/2311.07556
🔍 Our latest work: Deciphering GPT-4V on Knowledge-Intensive Visual Q&A, Link: arxiv.org/abs/2311.07536. 🌟 Explore how this powerhouse nails common sense, world knowledge, decision-making rationale, revealing its visual understanding, reasoning, and explanations. 🧠💡#GPT4V #AI
Beyond excited to publish our newest Weaviate Podcast with @Nils_Reimers! 🎙️🎉 Nils is one of my favorite people in the world to discuss Search with! Discussion topics include Cohere's Rerankers, Metadata, Long Doc Embeddings, RAG, and more!📚 youtube.com/watch?v=KITxQz…
Great news! “Efficient Transformers with Dynamic Token Pooling” has been accepted to #ACL23! We increase the efficiency *and* performance of Transformer LM by jointly segmenting and modelling language. @PontiEdoardo @AdrianLancucki @JChorowski 📜arxiv.org/abs/2211.09761
Great news! “Efficient Transformers with Dynamic Token Pooling” has been accepted to #ACL23! We increase the efficiency *and* performance of Transformer LM by jointly segmenting and modelling language. @PontiEdoardo @AdrianLancucki @JChorowski 📜arxiv.org/abs/2211.09761
It was a great pleasure to be in Cardiff to talk about ChatArena @_chatarena and future directions in multi-LLM collaboration.
It was a great pleasure to be in Cardiff to talk about ChatArena @_chatarena and future directions in multi-LLM collaboration.
🧠Determining the smartest LLM is a fascinating challenge! At ChatArena, we're working on creating game environments and a benchmark of their social capabilities. Excited to discuss this in the Weaviate Podcast with @CShorten30. Let's build this together: chatarena.org
🧠Determining the smartest LLM is a fascinating challenge! At ChatArena, we're working on creating game environments and a benchmark of their social capabilities. Excited to discuss this in the Weaviate Podcast with @CShorten30. Let's build this together: chatarena.org
Thrilled to have joined @CShorten30 on the Weaviate Podcast to discuss ChatArena! A fascinating platform enabling multiple #ChatGPT to engage in diverse game environments. Can't wait to see what the community can build by orchestrating multiple #LLMs in @_chatarena 🤖🗨️
Thrilled to have joined @CShorten30 on the Weaviate Podcast to discuss ChatArena! A fascinating platform enabling multiple #ChatGPT to engage in diverse game environments. Can't wait to see what the community can build by orchestrating multiple #LLMs in @_chatarena 🤖🗨️
Wait, did ChatGPT just solve prisoners' dilemma? 🤔
Wait, did ChatGPT just solve prisoners' dilemma? 🤔
I recently decide to change my twitter handle from @mindjimmy to @YuxiangJWu, because I realise that the old one is a bit confusing. Don't worry, I will keep posting interesting works and findings in AI, NLP and Large Language Models. #AI #LLM #GPT4 @_chatarena
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(((ل()(ل() 'yoav))).. @yoavgo
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Open Philanthropy @open_phil
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Helen Toner @hlntnr
21K Followers 1K Following Interests: China+ML, natsec+tech, brains+words+absurdity | Current: @CSETGeorgetown (opinions my own) | Former: @open_philMeta presents Layer Skip Enabling Early Exit Inference and Self-Speculative Decoding We present LayerSkip, an end-to-end solution to speed-up inference of large language models (LLMs). First, during training we apply layer dropout, with low dropout rates for
It's been exactly one week since we released Meta Llama 3, in that time the models have been downloaded over 1.2M times, we've seen 600+ derivative models on @huggingface and much more. More on the exciting impact we're already seeing with Llama 3 ➡️ go.fb.me/xsqzz8
Also check out our new paper: arxiv.org/abs/2404.05221 - A unified perspective of reasoning algorithms (which lies behind 🦙LLM reasoners) - AutoRace 🏁: automated _evaluation_ of LLM reasoning chains - Analysis of LLMs and reasoning algorithms (⛓️CoT, 🌲ToT, 🎶RAP, …)
Releasing 🔥LLM Reasoners v1.0🔥 🥇Popular library for advanced LLM reasoning - Reasoning-via-Planning (RAP)🎶 - Chain-of-Thoughts (CoT)⛓️ - Tree-of-Thoughts (ToT)🌴 - Grace decoding💄 - Beam search🔎 🥇Enhances #Llama3, GPT4, LLMs on @huggingface llm-reasoners.net
@WecoAI This tool sounds like a game-changer for simplifying machine learning code generation! Excited to see how AIDE can automate and streamline development processes.
Introducing AdvPrompter! 🚀Our new optimization technique that crafts prompt-dependent, human-readable adversarial suffixes in real-time, enhancing security for LLMs🛡️! 1️⃣Generate suffix in ~2 seconds, ~800x faster than methods like GCG and AutoDAN. 2️⃣Higher success rate, in…
New short course with @MistralAI ! Mistral's open-source Mixtral 8x7B model uses a "mixture of experts" (MoE) architecture. Unlike a standard transformer, an MoE model has multiple expert feed-forward networks (8 in this case), with a gating network selecting two experts at…
Nice to see performance measured on actual benchmarks instead of just reporting perplexity. Looks like a great resource for anyone building Language Models! 🙌
We have just released 🍷 FineWeb: 15 trillion tokens of high quality web data. We filtered and deduplicated all CommonCrawl between 2013 and 2024. Models trained on FineWeb outperform RefinedWeb, C4, DolmaV1.6, The Pile and SlimPajama!
Man, that’s one domain-specific LLM play I didn’t expect.
Llama3 reminds everyone of the misconception about scaling laws again: it's not that a larger model is always better, but that a larger model is cheaper to train if you want to reach the same performance. Yes, this might be somewhat counter-intuitive, but this is one of the key…
Llama 3 was trained using intra-document causal masking, as suggested by @yuzhaouoe's paper "Analysing The Impact of Sequence Composition on Language Model Pre-Training"! 🚀🚀🚀 arxiv.org/abs/2402.13991
So glad to share that I am one of the recipients of an @OpenAI Superaligment Fast Grant on the topic of #CoTfaithfulness 🥳🥳
The superalignment fast grants are now decided! We got a *ton* of really strong applications, so unfortunately we had to say no to many we're very excited about. There is still so much good research waiting to be funded. Congrats to all recipients!
Hey everyone! I am SUPER excited to publish our newest Weaviate podcast with Kyle Davis, the creator of RAGKit! 🎙️🔥 At a high-level, the podcast covers our understanding of RAG systems through 4 key areas: (1) Ingest / ETL, (2) Search, (3) Generate / Agents, and (4) Evaluation.…
So excited about integrating Weights & Biases with DSPy -- and showing how this helps you optimize RAG apps built with Cohere and Weaviate! 🔌😂👍 I am fascinated with how much more accessible optimization is becoming for building software applications. So cool to be…
Instead of having to manually write examples of your task (or examples of rationales when adding things like Chain-of-Thought prompting), DSPy orchestrates generating synthetic examples and controlling their quality. We are super happy to share an update on adding…
Excited to announce the Compass Beta, a very powerful multi-aspect data search system powered by a new embedding model, Compass. We're looking for help stress-testing the model's capabilities and finding where it breaks. Sign up here: txt.cohere.com/compass-beta/
Check out this Open-Source AI Data Scientist!! 🧑💻
Here you go, no more waitlisting and just run it locally! Local version of AIDE currently serves as a powerful tool for data scientists and machine learning engineers to explore draft designs.
Here you go, no more waitlisting and just run it locally! Local version of AIDE currently serves as a powerful tool for data scientists and machine learning engineers to explore draft designs.
We are open sourcing AIDE, a machine learning code generation agent. Simply describe the problem in natural language; the agent will begin experimenting on your local machine and then deliver the solution code. github.com/WecoAI/aideml
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