Yichen Jiang
@YichenJiang9
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Newly hooded PhD at UNC-Chapel Hill (@uncnlp) | @Apple AI/ML PhD Fellow | #NLProc | Working on Compositionality.
Chapel Hill, NC
Joined June 2019
We show Transformers generalize on complex data by using shared attention patterns for similar structures. BUT how to avoid overfitting on low-complexity data?. 🚨SQ-Transformer explicitly quantizes embeddings structurally & learns systematic attention. 🧵
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RT @yilin_sung: 🚀 New Paper: RSQ: Learning from Important Tokens Leads to Better Quantized LLMs. We show that not all tokens should be trea….
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Check out these other awesome works from my labmates & I will present my poster virtually on Aug22 --> "Inducing Systematicity in Transformers by Attending to Structurally Quantized Embeddings (". Detailed thread:Â #ACL2024nlp.
🚨 Check out an exciting batch of papers this week at #ACL2024!. Say hi to some of our awesome students & collaborators who are attending in person, and feel free to ask about our postdoc openings too 🙂. Topics: .-- multi-agent reasoning collaboration.-- structured
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RT @swarnaNLP: 🚨 New: my last PhD paper 🚨. Introducing System-1.x, a controllable planning framework with LLMs. It draws inspiration from D….
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RT @mohitban47: Having a great time at #LxMLS in Lisbon + meeting awesome people & exploring the beautiful city 🙂 (highly recommended ML sc….
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RT @swarnaNLP: We are going to present MAGDi at #ICML2024. If you are attending, say hi to @EliasEskin and @mohitban47 to know more about t….
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RT @shoubin621: Check out 2 useful updates on CREMA! 🚨. (1a) A new modality-sequential modular training for generalizable and efficient rea….
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Welcome to UNC NLP! I’m sure you will have a lot of fun doing interesting projects and living in a warmer place full of great college sports matches 😀 Best of luck!.
🥳Some of the first papers I read at the start of my ML journey were @mohitban47's papers on multimodal language understanding, and after a great couple of years at Northeastern working on vision-language, I'm excited to joining his lab at @uncnlp as a PhD student to work on
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Check out this work by my labmates on how to make LLMs not overly confident on bad answers. Spoiler 🚨: they made the model less confident on wrong data and more confident on correct ones.
🚨 Excited to share our new work on **confidence calibration** in LLMs!. LLMs are often badly calibrated & overconfident, explicitly (eg. "I'm 100% sure") and implicitly, eg. giving details/authoritative tone. We address both w/ a pragmatic speaker-listener multi-agent method.🧵
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RT @jaeh0ng_yoon: 🚨New paper👉RACCooN: remove/add/change video content effortlessly/interactively via our MLLM+Video Diffusion (V2P2V) frame….
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RT @shoubin621: 🚨 Introducing VideoTree! Captioning + LLMs can perform well on long-video QA, but dense frame captioning leads to inefficie….
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🎉Excited to announce that SQ-Transformer is accepted to #ACL2024nlp!. We induce systematicity & achieve stronger generalization in Transformers (w/o pretraining on complex data) by structurally quantizing word embedding & regularizing attention outputs. @XiangZhou14 @mohitban47.
We show Transformers generalize on complex data by using shared attention patterns for similar structures. BUT how to avoid overfitting on low-complexity data?. 🚨SQ-Transformer explicitly quantizes embeddings structurally & learns systematic attention. 🧵
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RT @swarnaNLP: Agentic workflows with LLMs are now getting popular for solving complex tasks!. In one of the early works on this topic -- R….
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Also, after 10 unforgettable years at Chapel Hill, 2 of those generously sponsored by @Apple Scholars in AIML PhD Fellowship, "I'm going to take my talents to Seattle and join Apple AIML". I will continue to do research in efficient and safe AI that generalizes compositionally.
Last weekend, I graduated from @unccs, 10 years after I wrote my first line of code in COMP 116. I'm super grateful to my advisor @mohitban47, labmates, intern mentors, and many others. Y'all can see how excited I was as I threw my cap out of the frame to the 2nd floor.
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Last weekend, I graduated from @unccs, 10 years after I wrote my first line of code in COMP 116. I'm super grateful to my advisor @mohitban47, labmates, intern mentors, and many others. Y'all can see how excited I was as I threw my cap out of the frame to the 2nd floor.
🎉🎓 Congratulations to these awesome new+old MURGeLab graduates on their hooding ceremony --> PhDs @peterbhase @yichenjiang9 @adyasha10 @swarnanlp (+ last year's @byryuer and @xiangzhou14, who joined us for this year's commencement) & MS @abhayzala7 🥳 . Was a fun celebration
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RT @mohitban47: 🚨 Check out an exciting set of #ICLR2024 papers/spotlights✨ this week at @iclr_conf (+workshop on reliable+responsible AI)!….
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RT @EliasEskin: 🎉 Excited that ReGAL has been accepted to @icmlconf #ICML2024! We use LLM-guided refactoring to discover reusable abstracti….
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RT @hanlin_hl: Can we design an efficient & versatile framework to reuse+adapt existing pretrained ControlNets to accurately guide any vide….
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RT @jmin__cho: Can we adaptively generate training environments with LLMs to help small embodied RL game agents learn useful skills that th….
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RT @JialuLi96: Can we teach multiple skills to a text-to-image (T2I) model (w/o expensive annotations), while minimizing knowledge conflict….
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RT @adyasha10: Can LLMs keep track of very long conversations?. We evaluate 'conversational memory' of LLMs via 3 tasks on our dataset of m….
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