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thomwolf

AI & ML interests

NLP and open-source :-)

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thomwolf's activity

upvoted an article about 1 hour ago
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FastRTC: The Real-Time Communication Library for Python

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New activity in m-ric/open_Deep-Research about 5 hours ago

Update app.py

#32 opened about 5 hours ago by
thomwolf
reacted to m-ric's post with πŸ€―πŸ‘πŸš€ about 13 hours ago
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2393
We now have a Deep Research for academia: SurveyX automatically writes academic surveys nearly indistinguishable from human-written ones πŸ”₯

Researchers from Beijing and Shanghai just published the first application of a deep research system to academia: their algorithm, given a question, can give you a survey of all papers on the subject.

To make a research survey, you generally follow two steps, preparation (collect and organize papers) and writing (outline creation, writing, polishing). Researchers followed the same two steps and automated them.

🎯 For the preparation part, a key part is find all the important references on the given subject.
Researchers first cast a wide net of all relevant papers. But then finding the really important ones is like distilling knowledge from a haystack of information. To solve this challenge, they built an β€œAttributeTree” object that structures key information from citations. Ablating these AttributeTrees significantly decreased structure and synthesis scores, so they were really useful!

πŸ“ For the writing part, key was to get a synthesis that's both short and true. This is not easy to get with LLMs! So they used methods like LLM-based deduplication to shorten the too verbose listings made by LLMs, and RAG to grab original quotes instead of made-up ones.

As a result, their system outperforms previous approaches by far!

As assessed by LLM-judges, the quality score os SurveyX even approaches this of human experts, with 4.59/5 vs 4.75/5 πŸ†

I advise you to read the paper, it's a great overview of the kind of assistants that we'll get in the short future! πŸ‘‰ SurveyX: Academic Survey Automation via Large Language Models (2502.14776)
Their website shows examples of generated surveys πŸ‘‰ http://www.surveyx.cn/
reacted to Kseniase's post with β€οΈβž•πŸ”₯πŸ‘ about 24 hours ago
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8 Free Sources about AI Agents:

Agents seem to be everywhere and this collection is for a deep dive into the theory and practice:

1. "Agents" Google's whitepaper by Julia Wiesinger, Patrick Marlow and Vladimir Vuskovic -> https://www.kaggle.com/whitepaper-agents
Covers agents, their functions, tool use and how they differ from models

2. "Agents in the Long Game of AI. Computational Cognitive Modeling for Trustworthy, Hybrid AI" book by Marjorie McShane, Sergei Nirenburg, and Jesse English -> https://direct.mit.edu/books/oa-monograph/5833/Agents-in-the-Long-Game-of-AIComputational
Explores building AI agents, using Hybrid AI, that combines ML with knowledge-based reasoning

3. "AI Engineer Summit 2025: Agent Engineering" 8-hour video -> https://www.youtube.com/watch?v=D7BzTxVVMuw
Experts' talks that share insights on the freshest Agent Engineering advancements, such as Google Deep Research, scaling tips and more

4. AI Agents Course from Hugging Face -> https://huggingface.co/learn/agents-course/en/unit0/introduction
Agents' theory and practice to learn how to build them using top libraries and tools

5. "Artificial Intelligence: Foundations of Computational Agents", 3rd Edition, book by David L. Poole and Alan K. Mackworth -> https://artint.info/3e/html/ArtInt3e.html
Agents' architectures, how they learn, reason, plan and act with certainty and uncertainty

6. "Intelligent Agents: Theory and Practice" book by Michael Wooldridge -> https://www.cs.ox.ac.uk/people/michael.wooldridge/pubs/ker95/ker95-html.html
A fascinating option to dive into how agents were seen in 1995 and explore their theory, architectures and agent languages

7. The Turing Post articles "AI Agents and Agentic Workflows" on Hugging Face -> https://huggingface.co/Kseniase
We explore agentic workflows in detail and agents' building blocks, such as memory and knowledge

8. Our collection "8 Free Sources to Master Building AI Agents" -> https://www.turingpost.com/p/building-ai-agents-sources
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New activity in nanotron/ultrascale-playbook 4 days ago

final final final typos

#72 opened 6 days ago by
thomwolf
New activity in nanotron/ultrascale-playbook 5 days ago

Typos

11
#80 opened 5 days ago by
iandanforth

How to download as pdf?

8
#74 opened 6 days ago by
vcoyk

dark-mode

9
#82 opened 5 days ago by
serhany