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Cheng-Fu Yang

@cfyang58

PhD @UCLANLP | prev. PE-AV & SAM @FAIR | Perception & Agents | On the job market
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Cheng-Fu Yang @cfyang58
🚀 Introducing OpenVLHarness:

Turn any LLM into an evidence-based reasoner that thinks and codes in visual space.

📈 GPT-6 Astra gains +9.9 points on average over 22 datasets.

⚡ Beats Codex and other VL harnesses by 7.7–8.5 points, at ≤37% of their cost.

🧵 More details ↓
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Cheng-Fu Yang @cfyang58
Thanks @_akhaliq for sharing our work!

👇 Try our interactive demo with your own LLM!

🎬 Demo: huggingface.co/spaces/uclanlp…
🔗 Website: openvlharness.github.io
📄 Paper: arxiv.org/abs/2610.26860
💻 Code: github.com/OpenVLHarness/…
huggingface.co OpenVLHarness - a Hugging Face Space by uclanlp Visual tool-use agent on your own model
AK Verified account @_akhaliq Oct 20
OpenVLHarness

Real World Visual Agentic Tool-Use with Multimodal Memory

paper: huggingface.co/papers/2610.26…
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Cheng-Fu Yang @cfyang58
Excited to share what I worked on this summer!

PE-AV — a new multimodal encoder trained on ~100M audio–video-text pairs!

✔️ Unified Audio–Video–Text embeddings
✔️ SOTA across audio, video & AV benchmarks

📄 Paper: go.meta.me/e541b6
💻 code: shorturl.at/X0Win
AI at Meta Verified account @AIatMeta Dec 18, 2025
We’re open-sourcing Perception Encoder Audiovisual (PE-AV), the technical engine that helps drive SAM Audio’s state-of-the-art audio separation.

Built on our Perception Encoder model from earlier this year, PE-AV integrates audio with visual perception, achieving state-of-the-art results across a wide range of audio and video benchmarks. Its native multimodal support can assist people in everyday tasks, including sound detection and richer audio-visual scene understanding.

🔗 Read the paper: go.meta.me/e541b6
🔗 Download the code: go.meta.me/7fbef0
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Cheng-Fu Yang @cfyang58
I'll be presenting our paper: Verbalized Representation Learning (VRL) on Tuesday 11-2 PM at #ICCV2025

Come see how models can automatically generalize compositionally to new knowledge — without labeled data or human effort!
📣 New Paper: Verbalized Representation Learning (VRL)

VRL bridges prompt engineering and representation learning to enable automatic interpretable feature extraction — all without gradient descent!

🔥 +29% over SOTA
📊 95% less data
arxiv.org/abs/2411.18651 @uclanlp
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Cheng-Fu Yang @cfyang58
I'll be presenting on Thursday 11-1 PM EST at #COLM2025.

Come see how we built self-evolving guardrails that address shifting norms and user feedback!
📣 Our paper “Customize Multi-modal RAI Guardrails with Precedent-based Predictions” has been accepted to #COLM2025! 🎉

TL;DR:
- No hand-crafting detailed rubrics
- Model auto-discovers and evolves its own rubrics
- Plug and play - work with OSS and commercial model
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