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giadap  authored a paper 4 days ago
INTIMA: A Benchmark for Human-AI Companionship Behavior
brunatrevelin  authored a paper about 2 months ago
Can AI be Consentful?
giadap  authored a paper about 2 months ago
Can AI be Consentful?
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AdinaY 
posted an update about 20 hours ago
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215
USO 🎨 Unified customization model released by Bytedance research

Demo
bytedance-research/USO
Model
bytedance-research/USO
Paper
USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning (2508.18966)

✨ Large-scale triplet dataset (content, style, stylized)
✨ Disentangled learning: style alignment + content preservation
✨ Style Reward Learning (SRL) for higher fidelity
✨ USO-Bench: 1st benchmark for style & subject jointly
✨ SOTA results on subject consistency & style similarity
AdinaY 
posted an update about 20 hours ago
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174
Step-Audio 2🔥 New end to end multimodal LLM for audio & speech, released by StepFun

stepfun-ai/step-audio-2-68b003c3a47b273fffaf67a8

✨ Direct raw audio: text & speech ,no ASR+LLM+TTS pipeline
✨ High-IQ reasoning: RL + CoT for paralinguistic cues
✨ Multimodal RAG + tool calling
✨ Emotion, timbre, dialect & style control
✨ SOTA on ASR, paralinguistic, speech dialog
giadap 
posted an update 1 day ago
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158
📊 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
AdinaY 
posted an update 4 days ago
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1010
🇨🇳 China’s State Council just released its “AI+” Action Plan (2025)

<The State Council’s Guidance on Deepened Implementation of the ‘AI+’ Strategy>
zh-ai-community/china-ai-policy-research

✨Goal: By 2035, AI will deeply empower all sectors, reshape productivity & society

✨Focus on 6 pillars:
>Science & Tech
>Industry
>Consumption
>Public welfare
>Governance
>Global cooperation

✨Highlights:
>Models: advance theory, efficient training/inference, evaluation system
>Data: high-quality datasets, IP/copyright reform, new incentives
>Compute: boost chips & clusters, improve national network, promote cloud standardization, and ensure inclusive, efficient, green, secure supply.
>Applications: AI-as-a-service, test bases, new standards
>Open-source: support communities, encourage contributions (incl. university credits & recognition), foster new application approaches, and build globally impactful ecosystems 👀
>Talent, policy & safety frameworks to secure sustainable growth
AdinaY 
posted an update 4 days ago
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4714
MiniCPM-V 4.5 🚀 New MLLM for image, multi-image & video understanding, running even on your phone, released by OpenBMB

openbmb/MiniCPM-V-4_5

✨ SOTA vision language capability
✨ 96× video token compression > high-FPS & long video reasoning
✨ Switchable fast vs deep thinking modes
✨ Strong OCR, document parsing, supports 30+ languages
AdinaY 
posted an update 4 days ago
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236
InternVL3.5 🔥 New family of multimodal model by Shanghai AI lab

OpenGVLab/internvl35-68ac87bd52ebe953485927fb

✨ 1B · 2B · 4B · 8B · 14B · 38B ｜ MoE → 20B-A4B · 30B-A3B · 241B-A28B 📄Apache 2.0
✨ +16% reasoning performance, 4.05× speedup vs InternVL3
✨ Cascade RL (offline + online) : stronger reasoning
✨ ViR: efficient visual token routing
✨ DvD: calable vision–language deployment
✨ Supports GUI & embodied agency 🤖
giadap 
authored a paper 4 days ago
AdinaY 
posted an update 9 days ago
AdinaY 
posted an update 9 days ago
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3595
Seed-OSS 🔥 The latest open LLM from Bytedance Seed team

ByteDance-Seed/seed-oss-68a609f4201e788db05b5dcd

✨ 36B - Base & Instruct
✨ Apache 2.0
✨ Native 512K long context
✨ Strong reasoning & agentic intelligence
✨ 2 Base versions: with & without synthetic data
AdinaY 
posted an update 11 days ago
AdinaY 
posted an update 11 days ago
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464
Before my vacation: Qwen releasing.
When I came back: Qwen still releasing
Respect!!🫡

Meet Qwen Image Edit 🔥 the image editing version of Qwen-Image by
@Alibaba_Qwen

Qwen/Qwen-Image-Edit

✨ Apache 2.0
✨ Semantic + Appearance Editing: rotate, restyle, add/remove 🎨
✨ Precise Text Editing → edit CN/EN text, keep style
meg 
posted an update 18 days ago
BrigitteTousi 
posted an update 18 days ago
BrigitteTousi 
posted an update 23 days ago
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476
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 23 days ago
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390
🤖 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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AdinaY 
posted an update 29 days ago
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1228
🔥 July highlights from Chinese AI community

zh-ai-community/july-2025-open-works-from-the-chinese-community-686586f1a8840797e477ae5a

✨ Another "DeepSeek moment" - Kimi K2 🙌

✨ Qwen goes fully matrixed - Instruct / Thinking / Coder models across 30B - 480B 🤯

✨ The multimodal wave🌊
- GLM-4.1V-Thinking: Image+Text > Text
- Intern-S1: Image+Text > Text
- Wan 2.2 - Text +Image > video
- Skywork-R1V3: Image+Text > Text
- Skywork-UniPic: Text > Image / Image > Text
- Tar-7B: Any-to-Any
- Ming-Lite-Omni-1.5: Any-to-Any
- Step3: Image+Text > Text
- HunyuanWorld-1: Image > 3D
- ThinkSound: Video > Audio
- Neta-Lumina: Text > Image

✨Tiny & deployable models 🤏
- SmallThinker runs on 1GB RAM

✨Agentic coding goes mainstream 💻
- Qwen3-Coder: fully spec'd tool calling
- GLM-4.5: browser agents, IDE assistant
- Qwen3 WebDev demo: text-to-frontend code

✨Domain-Specific & Utility Models/Tools/Dataset
- Science one S1: Scientific model
- Agentar DeepFinance: Finance dataset
- ObjectClear: Interactive Vision Tool
- Qwen3 MT Demo: Machine Translation Tool

✨ Big month not only for models, but for policy too🏛️
- Announced Global Action Plan for AI Governance
- Proposes to set up a World AI Cooperation Organization in Shanghai
- Released International AI Open Source Collaboration Initiative
- Published Risk Assessment Guidelines for Endpoint AI Agents

✨ Big event - WAIC
- 355K offline visitors
- 108 new released in 4 days
- 145 sessions across key domains

I’ve been tracking things closely, but July’s open-source wave still blew me away. Can’t wait to see what’s coming next! 🚀
meg 
posted an update 29 days ago
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462
🤖 👾 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.
AdinaY 
posted an update 30 days ago
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1644
Qwen team did it again!!

They just released Qwen3-Coder-30B-A3B-Instruct on the hub🔥
Qwen/Qwen3-Coder-30B-A3B-Instruct

✨ Apache 2.0
✨30B total / 3.3B active (128 experts, 8 top-k)
✨ Native 256K context, extendable to 1M via Yarn
✨ Built for Agentic Coding
AdinaY 
posted an update 30 days ago
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369
It’s here! After the WAIC announcement, StepFun has just dropped Step 3 🔥 their latest multimodal reasoning model on the hub.

Paper: Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding (2507.19427)
Model: stepfun-ai/step3

✨ 321B total / 32B active - Apache 2.0
✨ MFA + AFD : cutting decoding cost by up to 70% vs. DeepSeek-V3
✨ 4T image-text pretraining: strong vision–language grounding
✨ Modular, efficient, deployable: runs on just 8×48GB GPUs
AdinaY 
posted an update about 1 month ago
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3526
Qwen3-30B-A3B-Thinking-2507 🔥 latest step in scaling thinking capabilities from Alibaba Qwen team.

Qwen/Qwen3-30B-A3B-Thinking-2507-FP8

✨ 30B total / 3B active - Apache 2.0
✨ Native 256K context
✨ SOTA coding, alignment, agentic reasoning