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Recent Activity

giadap  authored a paper 7 days ago
INTIMA: A Benchmark for Human-AI Companionship Behavior
evijit  new activity 10 days ago
society-ethics/StableBias:Update README.md
yjernite  updated a collection 21 days ago
📊 Benchmarks and Leaderboards
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giadap 
posted an update about 2 hours ago
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I've noticed something. While we're careful about what we post on social media, we're sharing our deepest and most intimate thoughts with AI chatbots -- health concerns, financial worries, relationship issues, business ideas...

With OpenAI hinting at ChatGPT advertising, this matters more than ever. Unlike banner ads, AI advertising happens within the conversation itself. Sponsors could subtly influence that relationship advice or financial guidance.

The good news? We have options.
🤝 Open source AI models let us keep conversations private, avoid surveillance-based business models, and build systems that actually serve users first.

Read more about it in our latest blog post, co-written with
@frimelle
https://huggingface.co/blog/giadap/privacy-conversational-ai
giadap 
posted an update 4 days ago
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📊 We benchmark models for coding, reasoning, or safety… but what about companionship?

At Hugging Face, we’ve been digging into this question because many of you know how deeply I care about how people build emotional bonds with AI.

That’s why, building on our ongoing research, my amazing co-author and colleague @frimelle created the AI Companionship Leaderboard 🦾
frimelle/companionship-leaderboard

Grounded in our INTIMA benchmark, the leaderboard evaluates models across four dimensions of companionship:
🤖 Assistant Traits: the “voice” and role the model projects
🌷 Relationship & Intimacy: whether it signals closeness or bonding
💘 Emotional Investment: the depth of its emotional engagement
🤲 User Vulnerabilities: how it responds to sensitive disclosures

This work builds on our paper with @frimelle and @yjernite .

📢 Now we’d love your perspective: which open models should we test next for the leaderboard? Drop your suggestions in the comments or reach out! Together we can expand the leaderboard and build a clearer picture of what companionship in AI really looks like.

Paper: INTIMA: A Benchmark for Human-AI Companionship Behavior (2508.09998)
INTIMA Benchmark: AI-companionship/INTIMA
  • 1 reply
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giadap 
authored a paper 7 days ago
evijit 
in society-ethics/StableBias 10 days ago

Update README.md
#1 opened 10 days ago by
evijit
meg 
posted an update 21 days ago
BrigitteTousi 
posted an update 21 days ago
yjernite 
updated a collection 21 days ago
yjernite 
authored 3 papers 24 days ago
clem 
posted an update 25 days ago
BrigitteTousi 
posted an update 25 days ago
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486
New interactive viz from AI World showing OpenAI's new open model gpt-oss-120b breaking into the top 50 most liked models of all time on the Hub in under a day! ☄️☄️☄️
meg 
posted an update 26 days ago
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🤖 ICYMI: Yesterday, Hugging Face and OpenAI partnered to bring open source GPT to the public. This is a Big Deal in "AI world".

0. Common ground setting: OpenAI is the ChatGPT people. An “open source” model is one whose weights are available — that means the model can be “yours”.
1. You don’t have to interact with the company directly, nor give them your interactions, to use the system. The company can't "surveil" you.
2. You can evaluate the unique contributions of their SOTA model much more rigorously than you can when there are collections of models+code behind a closed API. You can find out specifically what the model can and can't do.
3. And you can directly customize it for whatever you'd like. Fine-tuning, wherein you give the model data that's tailored to your use cases and train it some more on that data, is trivial* when you have the model weights.
*Provided you have the compute.
4. You can directly benchmark whatever you'd like. Biases? Energy usage? Strengths/weaknesses? Go for it. You wants it you gots it--this transparency helps people understand SOTA *in general*, not just for this model, but points to, e.g., what's going on with closed Google models as well.
5. One of the most powerful things about "openness" that I've learned is that it cultivates ecosystems of collaborators building on top of one another's brilliance to make systems that are significantly better than they would be if created in isolation.
But, caveat wrt my own philosophy...
6. I do not take it as a given that advancing LLMs is good, and have a lot more to say wrt where I think innovation should focus more. For example, a focus on *data* -- curation, measurement, consent, credit, compensation, safety -- would deeply improve technology for everyone.
7. The transparency this release provides is massive for people who want to *learn* about LLMs. For the next generation of technologists to advance over the current, they MUST be able to learn about what's happening now. (cont...)
  • 1 reply
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meg 
posted an update about 1 month ago
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🤖 👾 Thanks so much to BBC News and the stellar Suranjana Tewari for having me on to talk about US <—> China relationship in AI, and what it means for AI ethics.
christopher 
updated a Space about 1 month ago
NimaBoscarino 
in society-ethics/lila_camera_traps about 1 month ago

Updated addresses of dataset files

1
#4 opened 11 months ago by
Saeid
giadap 
posted an update about 1 month ago
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3105
💬 From Replika to everyday chatbots, millions of people are forming emotional bonds with AI, sometimes seeking comfort, sometimes seeking intimacy. But what happens when an AI tells you "I understand how you feel" and you actually believe it?

At Hugging Face, together with @frimelle and @yjernite , we dug into something we felt wasn't getting enough attention: the need to evaluate AI companionship behaviors. These are the subtle ways AI systems validate us, engage with us, and sometimes manipulate our emotional lives.

Here's what we found:
👉 Existing benchmarks (accuracy, helpfulness, safety) completely miss this emotional dimension.
👉 We mapped how leading AI systems actually respond to vulnerable prompts. 👉 We built the Interactions and Machine Attachment Benchmark (INTIMA): a first attempt at evaluating how models handle emotional dependency, boundaries, and attachment (with a full paper coming soon).

Check out the blog post: https://huggingface.co/blog/giadap/evaluating-companionship

🚢 We also shipped two visualization tools with Gradio to see how different models behave when things get emotionally intense:
- AI-companionship/intima-responses-2D
- giadap/INTIMA-responses
christopher 
in society-ethics/lila_camera_traps about 1 month ago

How to access the dataset ???

2
#5 opened about 1 month ago by
pega0501
yjernite 
posted an update about 1 month ago
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𝗙𝗶𝗿𝘀𝘁 𝗚𝗣𝗔𝗜 𝗠𝗼𝗱𝗲𝗹 𝘄𝗶𝘁𝗵 𝗘𝗨 𝗗𝗮𝘁𝗮 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲? 🇪🇺

With the release of the EU data transparency template this week, we finally got to see one of the most meaningful artifacts to come out of the AI Act implementation so far (haven't you heard? AI's all about the data! 📊📚)

The impact of the template will depend on how effectively it establishes a minimum meaningful transparency standard for companies that don't otherwise offer any transparency into their handling of e.g. personal data or (anti?-)competitive practices in commercial licensing - we'll see how those play out as new models are released after August 2nd 👀


In the meantime, I wanted to see how the template works for a fully open-source + commercially viable model, so I filled it out for the SmolLM3 - which my colleagues at Hugging Face earlier this month 🤗 ICYMI, it's fully open-source with 3B parameters and performance matching the best similar-size models (I've switched all my local apps from Qwen3 to it, you should too 💡)

Verdict: congrats to the European Commission AI Office for making it so straightforward! Fully open and transparent models remain a cornerstone of informed regulation and governance, but the different organizational needs of their developers aren't always properly accounted for in new regulation. In this case, it took me all of two hours to fill out and publish the template (including reading the guidelines) - so kudos for making it feasible for smaller and distributed organizations 🙌 Definitely a step forward for transparency 🔍

To learn more have a look at:

- The SmolLM3 model: HuggingFaceTB/SmolLM3-3B
- Its filled out Public Summary of Training Content: hfmlsoc/smollm3-eu-data-transparency
- And if you're interested, some previous remarks on regulatory minimum meaningful standards for data disclosure: https://huggingface.co/blog/yjernite/naiac-data-transparency
BrigitteTousi 
posted an update about 1 month ago
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This is what Hugging Face is all about. We want everyone, hobbyists, researchers and industry alike, to be able to contribute to AI because everyone is affected by it. Kudos to HF's @irenesolaiman for spreading the word!🔥🤗