Hongyang Zhang @hongyangzh Twitter profile | Pikagi

Pikagi

Hongyang Zhang

@hongyangzh

1,931

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Assistant Professor @UWCheritonCS @VectorInst . Lead the SafeAI Lab. CMU ML PhD @SCSatCMU . @PKU1898 Alumni. Playing with Foundation Models.

Waterloo, Canada

https://t.co/S7myuvZmWo

Joined May 2018

Don't wanna be here? Send us removal request.

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@hongyangzh

Hongyang Zhang

11 months

Introduce EAGLE, a new method for fast LLM decoding based on compression: - 3x🚀than vanilla - 2x🚀 than Lookahead (on its benchmark) - 1.6x🚀 than Medusa (on its benchmark) - provably maintains text distribution - trainable (in 1~2 days) and testable on RTX 3090s Playground:

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@hongyangzh

Hongyang Zhang

3 years

[Students Hiring] Looking for multiple funded Master and PhD students at UWaterloo CS, working on 1) foundation of ML; 2) AI security; 3) trustworhty ML. The deadline is Dec 15. Please help spread the word or contact hongyang.zhang @uwaterloo .ca

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@hongyangzh

Hongyang Zhang

3 years

I am excited to announce that I will be joining @UWaterloo CS @UWCheritonCS as an tenure-track assistant professor and affiliated with @VectorInst in Fall 2021. I am very grateful to my advisors (Avrim, Nina, David, Greg, and @zicokolter ), friends, and colleagues. New Adventure!

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@hongyangzh

Hongyang Zhang

1 year

Just finished summer teaching of "Intro to ML" in @UWCheritonCS Update course with latest topics: transformer, LLM, alignment, AI safety, self-supervised learning, etc. Students are commenting good. Hope it is also helpful to the public. Syllabus:

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@hongyangzh

Hongyang Zhang

2 years

Though some of my papers got accepted, my favorite submission was rejected by ICML simply because "The reviews are not very insightful unfortunately", quoted from the 1st sentence in meta-review. Why should the authors pay for the low review quality? Ridiculous review system!!!

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@hongyangzh

Hongyang Zhang

9 months

🔥EAGLE v1.1 now supports gpt-fast with 6.5x🚀LLM inference What's new in v1.1: - ~2x🚀over gpt-fast (55.1 tok/s -> 100.2 tok/s) - Support Mixtral-8x7B with 1.5x🚀 - All done in <10 line code - Support bs>1 ⚒️Code: 🏅Benchmark: (on single RTX 3090 for

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@hongyangzh

Hongyang Zhang

3 years

Super excited that our team has won First Place Award (out of 1,558 teams) in the @CVPR 2021 Security AI Challenger (and $22,000🤑). Congratulations to the student Fangcheng whom I advise and Chao @PKU1898 . Stay tuned for our new methodology!

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@hongyangzh

Hongyang Zhang

7 months

A #ICML reviewer changes score 7->6->5 in 2 days after the score is released before we do rebuttal, quoted: "I initially gave a relatively high score, but after seeing other reviewers' comments, I think my score was a bit too high." Shouldn't the review be independent? Poisonous!

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@hongyangzh

Hongyang Zhang

4 years

Since everyone is showing off their NeurIPS acceptance, just be curious about one question: as there are ~2,000 accepted papers, what is the impact advantage of a NeurIPS accepted paper compared with an arXiv post?

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@hongyangzh

Hongyang Zhang

2 years

Though not at #ICML , it seems like I am attending it for real as everyone is tweeting about their papers. Might be more time- and money-saving to attend a conference on social media😅 Any one interested in organizing a ML conference on twitter?

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@hongyangzh

Hongyang Zhang

5 years

"Theoretically Principled Trade-off between Robustness and Accuracy" accepted to @icmlconf with high scores. The paper contains the winning strategies to NeurIPS'18 Adversarial Vision Challenge over all 400 teams. Don't miss it, and check it here

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@hongyangzh

Hongyang Zhang

6 months

EAGLE is accepted to #ICML2024 , together with: 1. AnyTool: 2. Dipmark: and an ACM CCS work: 3. zkLLM: Heading to Vienna #iclr : 4. RAIN: 5. See you all there!

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Unbiased Watermark for Large Language Models

The recent advancements in large language models (LLMs) have sparked a growing apprehension regarding the potential misuse. One approach to mitigating this risk is to incorporate watermarking...

@hongyangzh

Hongyang Zhang

11 months

Introduce EAGLE, a new method for fast LLM decoding based on compression: - 3x🚀than vanilla - 2x🚀 than Lookahead (on its benchmark) - 1.6x🚀 than Medusa (on its benchmark) - provably maintains text distribution - trainable (in 1~2 days) and testable on RTX 3090s Playground:

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@hongyangzh

Hongyang Zhang

5 years

New work with Avrim Blum, Travis Dick, Naren Manoj. Paper: … Code: … Comments welcome! We show that random smoothing---a SOTA defense with certified L_2 robustness---might be unable to certify L_p robustness for p>2. Intuition:

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@arxiv_cs_LG

cs.LG Papers

5 years

Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images. Avrim Blum, Travis Dick, Naren Manoj, and Hongyang Zhang

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@hongyangzh

Hongyang Zhang

11 months

EAGLE achieves SOTA results on various benchmarks. The method is also combinable with other parallelled techniques such as vLLM, Mamba, FlashAttention, quantization, and hardware optimization.

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@hongyangzh

Hongyang Zhang

2 years

2 presentations at #ICML : RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval: Building Robust Ensembles via Margin Boosting: Cannot attend in person. Happy to intro my collaborators or chat online. Looking forward!

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@hongyangzh

Hongyang Zhang

2 years

@shortstein @NeurIPSConf I think this mechanism is to avoid people bidding papers for each others and cheating. I have heard this for several years.

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@hongyangzh

Hongyang Zhang

8 months

We've just open-sourced the code for AnyTool! AnyTool is a (self-evolving, hierarchical) GPT-4 multi-agent system which can call as many as 16K+ APIs with ~60% accuracy.🚀📷 Code: Paper: Many thanks to Yu Du and Fangyun Wei for

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GitHub - dyabel/AnyTool

Contribute to dyabel/AnyTool development by creating an account on GitHub.

@omarsar0

elvis

9 months

LLM Agent for Large-Scale API Calls Cool research paper presenting AnyTool, an LLM-based agent that can utilize 16000+ APIs from Rapid API. Proposes a simple framework consisting of - a hierarchical API-retriever to identify relevant API candidates to a query - a solver to

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Hongyang Zhang

9 months

Honored to serve as the AE for the very first DMLR accepted paper (congrats to the authors). Please consider submitting your good work to DMLR (with only 3-month review window)!

@DMLRJournal

Journal of Data-centric Machine Learning Research

9 months

'Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift' by Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li Action Editor: Hongyang Zhang #Multimodal #Robustness #DistributionShift

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@hongyangzh

Hongyang Zhang

2 years

Though we faculty might not care 1 or 2 papers got accepted/rejected, students do care. It is very frustrating to them. There are 1,200+ accepted papers. I can imagine in ICML 2052, there are 1w+ papers. Perhaps at that time, arXiv would be the best place to submit to.

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@hongyangzh

Hongyang Zhang

1 year

Heading #ICML2023 . First in-person conf. after COVID. Thu: 1. A Law of Robustness beyond Isoperimetry 2. Understanding the Impact of Adv Robustness on Accuracy Disparity Sat: 3. PoT: Securely Proving Legitimacy of Training Data and Logic for AI Regulation See you all friends then

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@hongyangzh

Hongyang Zhang

3 years

UWaterloo CS is hiring new faculty this year! Please consider applying and help distribute the message. Feel free to let me know if there is anything I can help with.

@UWCheritonCS

Waterloo's Cheriton School of Computer Science

3 years

We’re hiring CS faculty! Join the Cheriton School of Computer Science, the top-ranked CS program in Canada for the second year in a row according to the recently released Maclean’s 2022 university rankings. See thread for the various academic appointments being sought. 1/5

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@hongyangzh

Hongyang Zhang

9 months

Thanks @omarsar0 for sharing. Excited to introduce AnyTool, a self-improving, hierarchical multi-agent system for 16K+ 🛠️ uses. AnyTool improves vanilla GPT-4's tool use ability by 2x ~ 8x pass rate. 📢More details will be upcoming about this exciting project.

@omarsar0

elvis

9 months

LLM Agent for Large-Scale API Calls Cool research paper presenting AnyTool, an LLM-based agent that can utilize 16000+ APIs from Rapid API. Proposes a simple framework consisting of - a hierarchical API-retriever to identify relevant API candidates to a query - a solver to

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@hongyangzh

Hongyang Zhang

1 year

RLHF? No! Releasing code: . RAIN is an inference (based on MCTS for harmless output) that allows LLMs to self-align *w/o finetuning*. The time overhead is ~4-fold of vanilla inference. It works well on HH,TurthfulQA,advBench (+15%↑). Comments are welcome!

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@omarsar0

elvis

1 year

LLMs Can Align Themselves without Finetuning? This paper discovers "that by integrating self-evaluation and rewind mechanisms, unaligned LLMs can directly produce responses consistent with human preferences via self-boosting" Does seem to have benefits in terms of generating

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@hongyangzh

Hongyang Zhang

3 years

@thegautamkamath Thank you, Gautam! Looking forward to the new adventure of being colleague with you!

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@hongyangzh

Hongyang Zhang

4 years

New blog by/with @yangarbiter @CyrusRashtchian @rsalakhu @kamalikac : We can mitigate the intrinsic trade-off between robustness and accuracy by looking at local Lipschitzness. Paper:

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A Closer Look at Accuracy vs. Robustness

Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. We take a...

@kamalikac

Kamalika Chaudhuri

4 years

Blog post: Both robustness and accuracy may be possible to achieve. w/ @yangarbiter @CyrusRashtchian @hongyangzh @rsalakhu

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@hongyangzh

Hongyang Zhang

2 years

Work done by 3 amazing Master students at @UWCheritonCS . Excited to share the work.

@sz_waterloo

Shufan Zhang

2 years

Thrilled to share our new work on the recovery problem for non-decomposable distances! – Check it out on arXiv: This is joint work with super talented colleagues Zhuangfei Hu and Xinda Li, under the advisory of @hongyangzh and David Woodruff. (1/n)

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@hongyangzh

Hongyang Zhang

3 years

@thegautamkamath This is a very popular movie across China in this spring festival. You are really a China expert!

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Hongyang Zhang

7 months

@matloff That is why by design, reviewers are not allowed to see others' in their initial review. Reviewers should not be influenced by others in the initial review, at least.

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@hongyangzh

Hongyang Zhang

2 years

Boosting is well-studied in natural training. How about its function in robustness? We show in #ICML2022 that boosting will help in robustness too by theory and practice. Joint work with @zdhnarsil , Aaron Courville, Yoshua Bengio, Pradeep Ravikumar and Arun Sai Suggala.

@zdhnarsil

Dinghuai Zhang 张鼎怀

2 years

Check our new ICML 2022 work on (adversarial) robust boosting and online learning! 🎉 Joint work w/ @hongyangzh , @AaronCourville , Yoshua, Pradeep and Arun.

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@hongyangzh

Hongyang Zhang

2 years

@thegautamkamath Why would faculty and senior Ph.D. accept a review invitation? They have no incentive but it takes them much time without learning anything. I know more and more high-qualified reviewers decline invitation. Our community needs to offer more reasons for them to serve.

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Hongyang Zhang

4 years

@krikamol I agree. But I am afraid the correctness cannot be guaranteed by the review system as well. Maybe "interesting" is one that matters.

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@hongyangzh

Hongyang Zhang

2 years

@roydanroy More severe issue is that reviewers are also bidding papers for each others. If so, there should be no bidding process in the reviewer-level as well.

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@hongyangzh

Hongyang Zhang

8 months

Great work! Glad to see EAGLE is on the top of the Spec-Bench for 7B model on RTX 3090 and larger models (13B and 33B) on A100.

@hemingkx

Heming Xia

8 months

🚨What is currently the best Speculative Decoding method for accelerating LLM inference?🔍 We introduce Spec-Bench📖: A Comprehensive Benchmark and Unified Evaluation Platform for Speculative Decoding!🚀 Project page: 🧵1/n

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Hongyang Zhang

3 years

@_vaishnavh I still remember the first day we met when both of us were first-year student at CMU. Anyway, congratulation!

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@hongyangzh

Hongyang Zhang

3 years

Looking forward to your very best submissions!

@huan_zhang12

Huan Zhang

3 years

#CallForPapers 📢: #ICLR2022 Workshop on Socially Responsible Machine Learning (➡️). We welcome all submissions on the fairness, privacy, security, equity and ethics of machine learning. Deadline🗓️Feb 25. Submit your paper📜at CMT: 🎉

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@hongyangzh

Hongyang Zhang

5 months

@abeirami @gowthami_s @tdietterich Thank you very much for mentioning our work, Ahmad😃

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@hongyangzh

Hongyang Zhang

11 months

@winglian Not necessary. Right now, we are training the head on the ShareGPT dataset (of course, you can use others), while ShareGPT is not the training data of LLaMA.

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@hongyangzh

Hongyang Zhang

6 months

@GuyZys @ai Sequence length of 2048 from the C4 dataset

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@hongyangzh

Hongyang Zhang

6 months

@heikkiarponen @GuyZys @ai 2048 tokens

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@hongyangzh

Hongyang Zhang

5 months

Thank you for posting our work!

@rohanpaul_ai

Rohan Paul

5 months

Interesting Paper - "EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty" 📌 Using gpt-fast, EAGLE attains on average 160 tokens/s with LLaMA2-Chat 13B on a single RTX 3090 GPU, compared to 24 tokens/s of Huggingface's implementations. 📌 Within the speculative

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@hongyangzh

Hongyang Zhang

3 years

@QuanquanGu Thank you, Quanquan. Hope to be as successful as you in the future :-)

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@hongyangzh

Hongyang Zhang

1 year

@hllo_wrld @UWCheritonCS @VectorInst @Canada welcome

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@hongyangzh

Hongyang Zhang

1 year

@YupengZhang7 @ECEILLINOIS Congrats

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@hongyangzh

Hongyang Zhang

11 months

@YiMaTweets Thank you, Yi!

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@hongyangzh

Hongyang Zhang

11 months

@junrushao On EAGLE, multi-round speculation can increase the speedup over vanilla by ~0.5. We will do more exact ablation study in the upcoming paper. Thanks for the question.

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@hongyangzh

Hongyang Zhang

2 years

@zdhnarsil @BorealisAI Congrats! tql

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@hongyangzh

Hongyang Zhang

7 months

@WilliamWangNLP That's why we should let everybody know and fight hard against this.

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@hongyangzh

Hongyang Zhang

7 months

@abeirami Congrats to the work!

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@hongyangzh

Hongyang Zhang

7 months

@roydanroy No proof in the paper. The reviewer admits he/she changes score just because of other reviews (perhaps low scores of his/her own paper).

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@hongyangzh

Hongyang Zhang

6 months

@L0GYKAL @ai @fede_intern Check this:

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@hongyangzh

Hongyang Zhang

9 months

@cHHillee Thank you for your great work as well, Horace! Let us know if gpt-fast team needs our help to merge EAGLE too.

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@hongyangzh

Hongyang Zhang

11 months

@JonJonJonWang Thanks for your kind word! EAGLE uses a trainable Transformer layer to guess the next token, not an mlp.

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@hongyangzh

Hongyang Zhang

3 years

@QuanquanGu @UCLAengineering @UCLAComSci @SloanFoundation Congratulations!

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@hongyangzh

Hongyang Zhang

5 months

@yubai01 @OpenAI Congrats, Yu!

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@hongyangzh

Hongyang Zhang

3 years

@UWCheritonCS Thank you!

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@hongyangzh

Hongyang Zhang

2 years

@weijie444 AI conferences should really consider your author self-ranking mechanism.

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@hongyangzh

Hongyang Zhang

3 years

@UWCheritonCS Thanks for RT😃

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@hongyangzh

Hongyang Zhang

4 years

@cvondrick @djhsu @ChengzhiM Very interesting work! Intuitively, is it because more tasks bring more training data, so the adversarial generalization is better and the robustness is strengthened?

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@hongyangzh

Hongyang Zhang

3 years

@Nthakur20 @UWaterloo Welcome!

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@hongyangzh

Hongyang Zhang

6 months

@hstyagi @ai All the calculations are in the finite field. Field has its own calculation system.

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@hongyangzh

Hongyang Zhang

6 months

@hstyagi @ai There is a quantization error as ZKP can only be done in a finite field. But as the field size increases, the error is small.

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@hongyangzh

Hongyang Zhang

6 months

@yuxiangw_cs @UCSanDiego @HDSIUCSD @ucsd_cse Wow! Congrats, Yu-Xiang.

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@hongyangzh

Hongyang Zhang

5 years

@RICEric22 @_leslierice @zicokolter Nice work! The overfitting issue might come from the empirical risk minimization, which can be alleviated by new training scheme (see Figure 4 in )

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@hongyangzh

Hongyang Zhang

2 years

@shortstein @NeurIPSConf Well. Perhaps the open review team should improve the matching system first😂

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@hongyangzh

Hongyang Zhang

3 years

@SimonShaoleiDu @NSF Congratulations

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@hongyangzh

Hongyang Zhang

6 months

@yuqirose Congrats!

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@hongyangzh

Hongyang Zhang

2 years

@peter_ljq OpenReview is too formal and aims for review, and doesn't allow one to attach pictures. Twitter perhaps is more casual, just like a poster session.

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@hongyangzh

Hongyang Zhang

2 years

@lintool @alexlimh23 @xueguang_ma @ji__xin Aha, thanks for inviting me to the project, Jimmy. Very pleasant experience working with you and your students.

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@hongyangzh

Hongyang Zhang

3 years

@anjalimiz hi @anjalimiz please check the following link:

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@hongyangzh

Hongyang Zhang

3 years

@rzshokri @IEEESSP @JPHubaux Congratulations!

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@hongyangzh

Hongyang Zhang

2 years

@CShorten30 Thanks. You are right; if the rotation is adversarial, traditional info retrieval algorithms will return totally different top 100 neighbors. Our goal is to make the algorithm robust. In this version, we focus on perturbation attack. It is interesting to study rotation as well.

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@hongyangzh

Hongyang Zhang

3 years

@alorebube Of course. Everyone has equal opportunity; the selection depends only on the background (e.g., research direction, taste, previous publications, reference letters, etc.) and whether background matches with me.

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@hongyangzh

Hongyang Zhang

2 years

@SurbhiGoel_ @PennCIS Congratulations!

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@hongyangzh

Hongyang Zhang

10 months

@haozhangml Thanks😀

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@hongyangzh

Hongyang Zhang

3 years

@jeffNegrea @WaterlooMath @VectorInst @DSI_UChicago Welcome!

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@hongyangzh

Hongyang Zhang

11 months

@billyuchenlin @_akhaliq Great work! Congrats.

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@hongyangzh

Hongyang Zhang

4 years

@CyrusRashtchian Tough question! My conjecture: current PAC-like ML framework cannot solve this issue, unless we have too many data. Maybe what we need is a more data-efficient framework, e.g., with knowledge, causal inference, new perception way, etc. Hopefully, tens of years later we will see.

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@hongyangzh

Hongyang Zhang

6 months

@maksym_andr @SebastienBubeck @zicokolter @KrzakalaF Congrats

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@hongyangzh

Hongyang Zhang

3 years

@xiaoransunpsu @UMNFSoS @jcmichener Congrats!

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@hongyangzh

Hongyang Zhang

3 years

@Usman_skhan Thank you!

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@hongyangzh

Hongyang Zhang

3 years

@weihu_ @UMich @UMichCSE @michigan_AI Congrats!

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@hongyangzh

Hongyang Zhang

8 months

@SimonShaoleiDu @SloanFoundation Congrats

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@hongyangzh

Hongyang Zhang

4 years

@CyrusRashtchian Looking forward to seeing new research that proves I am wrong😅

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@hongyangzh

Hongyang Zhang

2 years

@GuanyaShi @CarnegieMellon @CMU_Robotics @SCSatCMU @yisongyue Congrats!

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@hongyangzh

Hongyang Zhang

11 months

@tianle_cai Thank you, Tianle!

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@hongyangzh

Hongyang Zhang

2 years

@xnningxie @UofTCompSci @GoogleAI Congratulations

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@hongyangzh

Hongyang Zhang

5 years

@2prime_PKU Thanks for sharing!!! It seems very interesting.

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@hongyangzh

Hongyang Zhang

3 years

@yisongyue Thank you, Yisong! Looking forward to learning more from you about how to be an excellent professor in the future.

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@hongyangzh

Hongyang Zhang

5 months

@YiMaTweets @yaodong_yu Congrats to both of you! @yaodong_yu @YiMaTweets

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@hongyangzh

Hongyang Zhang

4 months

@zicokolter Congrats, Zico. Well-deserved.

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@hongyangzh

Hongyang Zhang

7 months

@rustyryan @roydanroy Rebuttal begins only when authors input their rebuttal. But what I mentioned is before authors do anything but the score has been released.

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@hongyangzh

Hongyang Zhang

2 years

@BeidiChen @CarnegieMellon @CMU_ECE @Meta @MetaAI My honor😆

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@hongyangzh

Hongyang Zhang

2 years

@YiMaTweets Same feeling here. The current review system is toxic and very misleading, especially to young students.

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@hongyangzh

Hongyang Zhang

9 months

@lihua_lei_stat @StanfordGSB Congrats

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@hongyangzh

Hongyang Zhang

6 months

@EdgarDobriban Congrats, Edgar.

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@hongyangzh

Hongyang Zhang

2 years

@priyald17 @MITEECS @ClimateChangeAI Congrats!

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@hongyangzh

Hongyang Zhang

2 years

@AineshBakshi @praveshkkothari Wow, congrats.

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@hongyangzh

Hongyang Zhang

3 years

@ast_eth @zhendongsu @acad_euro @ETH_en @CSatETH Congratulations, Zhendong! It is so well-deserved.

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@hongyangzh

Hongyang Zhang

6 months

@ai Thank you for posting!

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