Do NOT overhype OpenAI Operator
We show some failure modes that indicates it is almost surely below a college-level computer use.
My guess: OpenAI devoted a lot to post-train this model but not sufficiently pre-train it. The model does not even know some basic skills for browser use.
Blog link: https://t.co/SsGFv6Jw7d
Simulating human behavior with AI agents promises a testbed for policy and the social sciences. We interviewed 1,000 people for two hours each to create generative agents of them. These agents replicate their source individuals’ attitudes and behaviors. 🧵https://t.co/FOVcOQduXO
Cognitive biases in clinical decision-making lead to diagnostic errors. Our study shows that #LLMs, through a multi-agent framework, can help re-evaluate and correct misconceptions, enhancing diagnostic accuracy.
https://t.co/a3378Kc8iz
#AI#Healthcare#Diagnostics#MedTech
LLMs' political leaning and their potential influence on our democracy is a complex and important topic. Recent work including ours has shown left-leaning in top models in certain settings and their influence on voter choices through conversations (https://t.co/l4yF2b5Opa).
However, many crucial questions currently remain unanswered: What factors cause LLMs' left leaning? What goals should we set for these models? For example, should we pursue political neutrality in AI systems or some other goal(s), such as accuracy and/or pluralistic values? Is political neutrality even possible?
We call for the community to join and unite together to explore this space systematically to advance our scientific understanding in this important space:
https://t.co/i0PuBhj0Eg
We lay out the path forward and proposes future research questions in four broad areas: (1) evaluation of LLM political leanings, (2) understanding LLMs’ influences on our democracy, (3) better policy frameworks for AI development, and (4) technical solutions to mitigate political leanings.
As LLMs become increasingly integrated into society, continued investigation of how LLMs will reshape democracy is essential to maximize their benefits while minimizing risks to democratic processes.
👋 I'll be attending #EMNLP2024 in Miami Nov 11 - 17.
😆 I'd like to chat and learn more about: #EducationalDataMining; LLM Reasoning and Planning; #Causality / Intervention in NLP; Low-Resource LM...
📜 Our Poster Nov 14 14:00-15:30 Jasmin Rm:
https://t.co/VANrriby9S
🌐 Are LLM agents prepared to navigate the rich diversity of cultural and social norms? 🏠 CASA tests them on real-world tasks like online shopping and social discussion forums, revealing that current agents show less than 10% awareness and over 40% norm violations.
🧠 We’re bridging this gap by combining fine-tuning on regional data with strategic prompts to create agents that better understand our world’s diversity.
Read the full paper for all insights! 📑https://t.co/OKBQ8UfIKd
Grateful for the incredible team at Salesforce AI Research @salesforce !
🚀 New paper on LLM reasoning 🚀 We present MathGAP, a framework for evaluating LLMs on math word problems with arbitrarily complex proof structures--resulting in problems that are challenging even for GPT-4o and OpenAI o1 💥 A thread 🧵
https://t.co/2k7CpIGtUv
It's common to add personas in system prompts, assuming this can help LLMs. However, through analyzing 162 roles x 4 LLMs x 2410 questions, we show that adding a persona mostly has *no* statistically significant difference from the no-persona setting. If there is a difference, it is *negative*. It's time to rethink the usage of personas in system prompts!
🙋♂️ I am in Boise for #CIKM2024
👉 interested in the broad topics of applications of LLMs for communication and education; reasoning, interpretability & causality; self-supervised learning... Let's chat about it!
Our work to share ⏬ https://t.co/YwYRLCTssm
It’s not safe to say LLMs do NOT reason. If they insist on using all the conditions whether relevant or irrelevant, it may because they really want to follow all the instructions they are given.
Exciting News! Our new paper on memorization in text-to-image diffusion is now available. We delve into the understanding of memorization via attention, and throw a light on the internal model behavior when memorization happens. Please find our paper at https://t.co/BEZ9EXfM2X
You may know gene language models, but what about cell language models? We just published a blog on Valence Portal about our ICLR 2024 paper CellPLM: Pre-training of Cell Language Model Beyond Single Cells. Check it out📷: https://t.co/t86FoeKoPN
#AcademicJobs#FacultyHiring Emory University's CS Department seeks passionate and innovative individuals to join our faculty team! We're inviting applications for positions at all ranks. Retweet appreciated!
Discover more about the application process: https://t.co/tSYxAsWSmu
Check our efforts on incorporating LLM on Graph. Our repository is efficient and easy to use for your next step research. Welcome to star and follow! https://t.co/5RlDEOr0Hj
Our latest preprint in single-cell analysis, CellPLM, is now available!
Highlights:
- 🏅️The first of its kind in encoding cell-cell relations.
- 🚀 100x faster inference speed than existing pre-trained models.
- 🏆 SOTA performance in various downstream tasks.
GREAT NEWS‼️
I'll be joining Morgan State University @MorganStateU as an Assistant Professor in Computer Science starting September 2023! Grateful for this opportunity and thankful to both my advisor @tangjiliang and labmates @dse_msu for their continued support. #NewBeginnings