Xia “Ben” Hu @huxia
Associate Professor of CS@Rice working on AutoML, XAI and Network Analytics. Author of AutoKeras and NCF. cs.rice.edu/~xh37/index.ht… Houston, TX Joined September 2009-
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📢Postdoc Position📢 Dr. Xia Hu @huxia and I are looking for a Chairman's Postdoctoral Fellow in Efficient and Trustworthy LLMs @RiceCompSci If you are interested, please do not hesitate to apply: docs.google.com/document/d/1Ks…
Without fine-tuning, Self-Extend has significantly improved performance of the Gemma-2b-it performance in the needle in the haystack task, increasing its capability from less than 8k (pretraining window) to over 90k!! lnkd.in/gD_DqJvi
Without fine-tuning, Self-Extend has significantly improved performance of the Gemma-2b-it performance in the needle in the haystack task, increasing its capability from less than 8k (pretraining window) to over 90k!! lnkd.in/gD_DqJvi
Excited to introduce KIVI🥝, the first 2bit KV cache quantization breakthrough! 🚀 KIVI can be directly integrated into existing LLMs without any tuning. 📄 Paper: arxiv.org/abs/2402.02750 💻 Code: github.com/jy-yuan/KIVI #KIVI #LLM #AI #MachineLearning
Welcome more people to trying Self-Extend/LongLM on more diverse tasks and models to see when it works and identify its limitations. Here is our implementation github.com/datamllab/Long… . Credits to @serendip410 !
Welcome more people to trying Self-Extend/LongLM on more diverse tasks and models to see when it works and identify its limitations. Here is our implementation github.com/datamllab/Long… . Credits to @serendip410 !
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning With only four lines of code modification, the proposed method can effortlessly extend existing LLMs’ context window without any fine-tuning. arxiv.org/abs/2401.01325
Here you go: Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arxiv.org/abs/2304.13712
Here you go: Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arxiv.org/abs/2304.13712
Should we use LLMs or fine-tuned models for downstream tasks? If you are interested in this question, please take a look: Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arxiv.org/abs/2304.13712
The success of LLMs relies on vast amounts of high-quality data. We've analyzed from a data-centric AI perspective. Stay tuned! @TDataScience towardsdatascience.com/what-are-the-d…
🤝 Companies and organizations seeking research solutions to their data science and artificial intelligence challenges can partner with the D2K Lab at @RiceUniversity to sponsor a capstone team. Learn about the D2K Capstone at bit.ly/3laOXHW
Curious about what "data-centric AI" is? Our comprehensive survey delves into the increasingly important role of data in building AI systems, including the recent waves of LLMs. Check it out! arxiv.org/abs/2303.10158 #AI #MachineLearning #LLMs
The paper submission deadline is in 5 days!⏳Check out the CFP and submit at chilconference.org by Feb 15th, 11:59pm ET
We recently wrote an article discussing the following questions: 1) Whether LLM-generated texts could be detected? 2) How to detect? 3) Opportunities and concerns moving forward. Please take a look at the Medium article, the paper will be out next week. medium.com/@rxtang/the-sc…
Check it out if you are interested in outlier detection lnkd.in/eAbz_ng
Check it out if you are interested in outlier detection lnkd.in/eAbz_ng
A recent work on Trojan Attack on Deep Nets, certainly I like the title :) Paper: arxiv.org/pdf/2006.08131… Codes: github.com/trx14/TrojanNet
After much consideration, the General Chairs, Executive Committee and Organizing Committee for KDD 2020 have decided to take the conference fully virtual. The events of the past few months and the continued safety concerns have led us to make this difficult decision.
Excellent data on COVID-19 just published in Nature: nature.com/articles/s4159…
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1K Followers 457 Following robots. twin boys. the academy. @RiceUniversity @RiceEngineering @RiceMECH Prof of Mech Eng, ECE, BIOE, and CS; Chair, Dept of Mechanical Engineering📢Postdoc Position📢 Dr. Xia Hu @huxia and I are looking for a Chairman's Postdoctoral Fellow in Efficient and Trustworthy LLMs @RiceCompSci If you are interested, please do not hesitate to apply: docs.google.com/document/d/1Ks…
We updated #SmoothQuant to accelerate newer LLMs:
🚀 Updated our #SmoothQuant paper! Now showing it works on newer LLMs like Llama-2, Falcon, Mistral, & Mixtral with W8A8 quantization & negligible loss. Check our paper if you want to reduce LLM serving costs! 📄: arxiv.org/pdf/2211.10438…
Thanks for sharing! It's a great reminder that, despite the challenges, our work is gaining attention. Recently, we released FlashAttention support for SelfExtend (github.com/datamllab/Long…, credits to @qingquan_song!). We're also working diligently to implement triton-based…
Thanks @LangChainAI for giving a shout-out to our self-extend! arxiv.org/abs/2401.01325 Excellent work led by @serendip410
FlashAttention Support for Self-extend! Give it a try!
Thanks for sharing! It's a great reminder that, despite the challenges, our work is gaining attention. Recently, we released FlashAttention support for SelfExtend (github.com/datamllab/Long…, credits to @qingquan_song!). We're also working diligently to implement triton-based…
Thanks @LangChainAI for giving a shout-out to our self-extend! arxiv.org/abs/2401.01325 Excellent work led by @serendip410
RAG for long context LLMs: Video Will long context LLMs really kill RAG? This is a talk @RLanceMartin gave at a few recent meetups that pulls together threads from a few different projects related to this question. Multi-needle in a haystack shows limitations in long-context…
Despite the mixed feelings about Google's latest Gemma model, we're big fans! @GoogleAI Why? Coz we found it pairs incredibly well with our SelfExtend 🤣🤣🤣 - like, perfectly! With Self-Extend, no fine-tuning needed, we effortlessly expanded Gemma's window from 8k to 90k+! On…
Amazing results for Gemma model with Self-Extend!!!
Despite the mixed feelings about Google's latest Gemma model, we're big fans! @GoogleAI Why? Coz we found it pairs incredibly well with our SelfExtend 🤣🤣🤣 - like, perfectly! With Self-Extend, no fine-tuning needed, we effortlessly expanded Gemma's window from 8k to 90k+! On…
Excited to introduce KIVI🥝, the first 2bit KV cache quantization breakthrough! 🚀 KIVI can be directly integrated into existing LLMs without any tuning. 📄 Paper: arxiv.org/abs/2402.02750 💻 Code: github.com/jy-yuan/KIVI #KIVI #LLM #AI #MachineLearning
llama.cpp now supports Self-Extend basic fact extraction tests with ~8k context and base LLaMA 7B v2 (train context of 4096) and the context extension seems to work. github.com/ggerganov/llam…
With the recent release of #TinyLlama, SLMs have attracted a lot of attention. I re-released my previously trained SLM - LiteLlama under the MIT license, which has 460M parameters trained with 1T tokens. I hope to contribute a bit to the community. huggingface.co/ahxt/LiteLlama…
So cool - this is one of the simplest, clearest, cleverest papers I've seen in a while. In 4 lines of code, the authors extend context windows by remapping OOC token positions at inference. arxiv.org/abs/2401.01325 LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning With only four lines of code modification, the proposed method can effortlessly extend existing LLMs’ context window without any fine-tuning. arxiv.org/abs/2401.01325
We conducted 45,079 experiments in total to investigate the most representative fairness method (maybe not the most recent method). Check out our paper for details and findings. Joint work with @jianfengchi, hugo chen, Qifan Wang,@hanzhao_ml, Na Zou, @huxia.
After speeding through the faculty tenure process in only six years — while launching his successful startup @ThirdAILab — @Anshumali_ Shrivastava has been recognized by the deans of Rice University with the Charles W. Duncan Jr. Achievement Award for Outstanding Faculty.
Just landed Kigali🇷🇼. See you soon at #ICLR2023 in person.
Very proud that my PhD students win two major graduate research award at the ECE department award ceremony. Congratulate Yushun Dong for receiving the Louis T. Rader Graduate Research Award and Song Wang for receiving the Ann Lee Brown Rookie of the Year Award @uvaece
This is our original thread
Should we choose to use LLMs or smaller finetuned models in practical use cases? Take a look at our survey arxiv.org/abs/2304.13712 , which covers NLU tasks, Generation tasks, Knowledge-intensive tasks, abilities regarding scaling, some miscellaneous and real-world tasks.
We've updated the still version of the LLM evolutionary tree. Add more models and correct several typos. Go for a check! github.com/Mooler0410/LLM… Our survey: Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arxiv.org/abs/2304.13712
@DrJimFan thanks. The authors are @JingfengY @serendip410 @RuixiangT Qizhang Feng Bing Yin @huxia .
@DrJimFan Welcome to check out paper as well 😃 arxiv.org/abs/2304.13712
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