Lifu Huang
@lifu_huang
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Assistant Professor in the Computer Science Department at UC Davis(@ucdavis), director of PLUM_Lab (@LabPlum), focusing on #NLP, #Multimodal, #AI4Science
Davis, CA, USA
Joined March 2013
💡Call to Action: - Submit your work and showcase your contributions! - Published in this field? We’d love to hear from you—apply to give a talk and inspire the community!
We are thrilled to announce a series of AI4Science workshops at ICLR'25, WWW'25, and AAAI Spring Symposium! Whether you're exploring cutting-edge AI techniques for scientific discovery or pushing the boundaries of interdisciplinary research, these workshops are perfect for you!
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We are thrilled to announce a series of AI4Science workshops at ICLR'25, WWW'25, and AAAI Spring Symposium! Whether you're exploring cutting-edge AI techniques for scientific discovery or pushing the boundaries of interdisciplinary research, these workshops are perfect for you!
🌟Call for Papers: Agentic AI for Science Workshop at The Web Conference 2025!🌟 Updated Submission Deadline: January 15, 2025 (11:59 PM AoE) Submission Website: Workshop Website:
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Excited about how AI/LLMs are revolutionizing our daily research activities? 🚀Join us at IJCAI'24 (@IJCAIconf) for our "AI4Research" workshop, with an incredible lineup of keynote speakers! Don't miss out! #AI4Research #IJCAI24 #callforpapers
🎉 Get set for the ultimate brain boost at the "AI4Research" workshop ( in Jeju, Korea, alongside IJCAI'24! 🧠💥 Dive into the latest AI breakthroughs in accelerating & automating research. Submit your papers by May 20th 🚀 @IJCAIconf
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📢 Call for Papers! We invite all submissions related to NLP and look forward to fostering connections among NLP researchers from diverse universities and backgrounds!! #NLP #CFP #SouthNLP2024
We are delighted to announce that the First South NLP Symposium will take place on March 29, 2024, at Emory University: Here are the details regarding the call for papers: We look forward to seeing you at the symposium.
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#EMNLP2023: Imagine how you solved math problems you have never seen before 🤔🤔 Inspired by a similar human thinking process, we proposed ✨SOCRATIC QUESTIONING✨, a new divide-and-conquer algorithm to elicit complex reasoning in LLMs beyond Chain-of-Thought or Tree-of-Thought
Our new work ✨The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language Models✨ is accepted to #EMNLP2023. Inspired by the human cognitive process, we propose SOCRATIC QUESTIONING, a divide-and-conquer style algorithm that mimics the 🤔recursive thinking process.
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RT @SanghaniCtrVT: In an interview w/@researchvoyage Ph.D. student @barry_yao0 discusses his work @SanghaniCtrVT that garnered Best Paper A…
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RT @SanghaniCtrVT: Ph.D. student @zhiyangx11 @SanghaniCtrVT introduces and shares a new dataset that researchers and practitioners can leve…
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✨Vision-Flan✨-- Try it out if you are curious about how much we can push it forward for visual instruction tuning and what problems are still remaining
Today we officially release ✨Vision-Flan✨, the largest human-annotated visual-instruction tuning dataset with 💥200+💥 diverse tasks. 🚩Our dataset is available on Huggingface 🚀 For more details, please refer to our blog
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RT @SanghaniCtrVT: Congrats to @zhiyangx11 @YingShen_ys @lifu_huang @VT_CS @SanghaniCtrVT who received an Outstanding Paper Award @aclmeeti…
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Wow! Excited to share that our MultiInstruct ( work was selected for the outstanding paper award of ACL'2023! Many thanks to the best paper committee and Congrats to my awesome students @zhiyangx11 @YingShen_ys
My first ever submission to ACL was selected by the #ACL2023 best paper committee for the 🏆outstanding paper award🏆 Huge thanks to the reviewers and committee members for recognizing our contributions. Congrats to my advisor @lifu_huang and collaborator @YingShen_ys
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My **favorite** work in the line of continual learning for information extraction (from our awesome @minqian_liu ), with many insights and super-encouraging results! Welcome to check it out at #ACL2023!
Struggling with catastrophic forgetting when updating your model? 🤯 Check out our latest work to appear at Findings of 🌟#ACL2023NLP🌟! We extensively study the *classifier drift* issue in continual learning and introduce an effective framework for this problem. 📌paper at 🧵 (1/n)
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