Yu Su(@ysu_nlp) 's Twitter Profileg
Yu Su

@ysu_nlp

Dist. Assist. Prof.@OhioState, Director @osunlp, 20% Researcher@Microsoft. I like to think about intelligence, artificial or biological

ID:1240355312

linkhttp://ysu1989.github.io calendar_today04-03-2013 02:58:16

950 Tweets

5,9K Followers

858 Following

Yu Su(@ysu_nlp) 's Twitter Profile Photo

Glad to see MMMU being integrated into HELM. Gemini 1.5 Pro working (slightly) better than GPT-4V is aligned with our experience in using these models in various vision-language tasks

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Zeyi Liao(@LiaoZeyi) 's Twitter Profile Photo

Alert 🚨🚨:
We have released our adversarial suffixes generators (AmpleGCG-series models) on Huggingface (huggingface.co/osunlp/AmpleGC…).
Our generated adversarial suffixes on AdvBench and MaliciousInstruct can be accessed via Google form (docs.google.com/forms/d/1P8hxs…).
In light of ethical…

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Yu Su(@ysu_nlp) 's Twitter Profile Photo

The absolute number is meaningless when it comes to publications, but this is a really proud advisor moment: We OSU NLP Group started submitting to ML conferences last year. In the past cycle, we had 3 NeurIPS, 5 ICLR, and 4 ICML accepted. How lucky I am to work with so many amazing…

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Jian Xie @ ICLR2024(@jianxie_) 's Twitter Profile Photo

I will be attending ICLR2024 in Vienna next week and presenting our three accepted papers, including 'Knowledge Conflicts in the RAG Scenario', 'Efficient Instruction Tuning Dataset Construction', and 'A Complex Planning Benchmark for Language Agents'.

See the details 👇

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Yu Su(@ysu_nlp) 's Twitter Profile Photo

I observe the same and thought a bit about that. I'm actually sympathetic to this 'abuse' of 'reasoning'.

Humans have multiple and relatively distinct (though still overlapping) cognitive faculties such as perceptual inferences, intuitive inferences, and reasoning (in the…

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Michael Black(@Michael_J_Black) 's Twitter Profile Photo

In case you can't read this blog post about startups and research on Medium, I've posted a version to the Perceiving Systems blog also: perceiving-systems.blog/en/post/ai-sta…

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Yu Su(@ysu_nlp) 's Twitter Profile Photo

Quoting Yi Ma 'It is industry's job to find how to do better, but academia is to find out how to do it right.' While I think there're lots of good industry research doing things right, when it comes to reseach on agents, I do think academia has unique freedom to explore how…

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Graham Neubig(@gneubig) 's Twitter Profile Photo

We're having a big event on agents at CMU on May 2-3 (one week from now), all are welcome! cmu-agent-workshop.github.io

It will feature:
* Invited talks from Alane Suhr / suhr @ sigmoid . social Yu Su Xinyun Chen Maarten Sap (he/him) and Chris Paxton
* Posters of cutting edge research
* Seminars and hackathons

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Thomas Wolf(@Thom_Wolf) 's Twitter Profile Photo

Llama3 was trained on 15 trillion tokens of public data. But where can you find such datasets and recipes??

Here comes the first release of 🍷Fineweb. A high quality large scale filtered web dataset out-performing all current datasets of its scale. We trained 200+ ablation…

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Yi Ma(@YiMaTweets) 's Twitter Profile Photo

Talking to many junior faculty members and students in AI lately. Many seem to be somewhat lost with all the seemingly fast progresses made by the industry. My suggestion to them is: It is industry's job to find how to do better, but academia is to find out how to do it right.

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Reka(@RekaAILabs) 's Twitter Profile Photo

We evaluate Core on standard benchmarks for both text and multimodal, along with a blind third-party human evaluation.

We evaluate Core on standard benchmarks for both text and multimodal, along with a blind third-party human evaluation.
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Yu Su(@ysu_nlp) 's Twitter Profile Photo

These folks Tao Yu ✈️ ICLR 2024 Tianbao Xie✈️ICLR etc. are serious when it comes to agent benchmarks. Excited to have an agent benchmark with an OS simulator to play with!

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Microsoft Research(@MSFTResearch) 's Twitter Profile Photo

In this issue: LLMs in the Imaginarium: Tool Learning through simulated trial and error; Benchmarking LLMs across languages, modalities, models and tasks; Training audio captioning models without audio. msft.it/6016cIfvY

In this issue: LLMs in the Imaginarium: Tool Learning through simulated trial and error; Benchmarking LLMs across languages, modalities, models and tasks; Training audio captioning models without audio. msft.it/6016cIfvY
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Yu Su(@ysu_nlp) 's Twitter Profile Photo

I whole-heartedly second Nando de Freitas 🏳️‍🌈’s recommendation. This is THE book I recommend to my students OSU NLP Group interested in getting a first conceptual framework about what is intelligence and how it comes about from evolution.

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Lingbo Mo(@LingboMo) 's Twitter Profile Photo

🔍 In the past year, there has been a surge in the release of open-source LLMs, making them easily accessible and showing strong capabilities. However, the exploration of their trustworthiness remains much limited, compared to proprietary models. A natural question to ask is:…

🔍 In the past year, there has been a surge in the release of open-source LLMs, making them easily accessible and showing strong capabilities. However, the exploration of their trustworthiness remains much limited, compared to proprietary models. A natural question to ask is:…
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Jaylen Jones(@Jaylen_JonesNLP) 's Twitter Profile Photo

Counter narratives directly challenge hate speech while limiting free speech infringement concerns. Automatic generation approaches are crucial due to the constant influx of toxic content online; yet, evaluating these systems is challenging. Can LLM-as-a-Judge strategies allow…

Counter narratives directly challenge hate speech while limiting free speech infringement concerns. Automatic generation approaches are crucial due to the constant influx of toxic content online; yet, evaluating these systems is challenging. Can LLM-as-a-Judge strategies allow…
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