@NeurIPSConf Last year, only 40 papers out of near 700 papers were accepted (<6%). Is there any change in the acceptance policy (ie, limited number of papers or very small acceptance rate, like 2025)?
📄 Pre-print (arxiv): https://t.co/GYY5fVCxLe
🌐 Project page: https://t.co/uCkgelUVKo
💻 Code: check our project page!
This is a joint work with Unsal Ozturk and Sébastien Marcel. Congratulations to the team! 🚀
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#bias#fairness#LLM#VLM#MLLM
Multimodal LLMs are rapidly being adopted for vision-language tasks applications. But how fair are they across demographic groups?🤔
🔍In our recent work, accepted in #CVPR 2026 workshops, we evaluate gender and ethnicity bias in 9 different MLLMs for face verification.
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📊Key findings:
✅ Bias persists in MLLMs: Performance varies significantly across demographic groups
✅ Gender and ethnicity disparities can be observed even in advanced models
✅ There is a gap between generative capability and trustworthy decision-making
🧵(2/3)#bias#fairness
🚨 Deadline Extension! 🚨
The submission deadline for @CVPR Workshop on Foundation and Generative Models in Biometrics is extended to March 10.
🌐 Visit the workshop page for more details and call for papers: https://t.co/QLapcQaGnz
#CVPR#CVPR26#CVPR2026
📢Thrilled to announce that we are organising the 2nd Workshop on Foundation and Generative Models in Biometrics at #CVPR 2026 !
📍Denver, USA - @CVPR
🗓️June 3-4, 2026
🔍More details and call for papers: https://t.co/QLapcQaGnz
✨Paper spotlight!
The paper provides an in-depth analysis of state-of-the-art methodologies regarding foundation multi-modal models, their advancements, and their applicability to biometrics tasks.
🔗Read at https://t.co/1ztPbWXkjQ.
Excited to share our new paper, "FaceLLM: A Multimodal Large Language Model for Face Understanding" ! ✨
📄 Pre-print(arxiv): https://t.co/7Et8FNt4ad
🌐 project page: https://t.co/JwzsWLK5PB
We introduce FaceLLM, a MLLM trained specifically for facial image understanding. To construct the training data, we propose a novel weakly supervised pipeline that generates high-quality question-answer pairs based on images from the FairFace dataset.
🚨 Deadline Extension! 🚨
The submission deadline for #ICCV2025 Workshop on Foundation and Generative Models in Biometrics is extended to July 1. @ICCVConference#ICCV
🔍Visit the workshop page for more details and call for papers: https://t.co/GThMMCUktq
📢We are thrilled to announce that we are organising the Workshop on Foundation and Generative Models in Biometrics at #ICCV 2025 !
📍Honolulu, Hawaii - @ICCVConference
🗓October 19-20, 2025
#ICCV2025
🔍More details and call for papers: https://t.co/GThMMCUktq
🧵(4/4) We also show that our approach can be used to mitigate leakage from the generator's training set and explore the ability of generative models to generate data beyond it. #ICML#ICML2025
Excited to share that our paper is accepted at #ICML 2025 !
We introduce a novel physics-inspired approach based on Brownian motion to generate synthetic face recognition datasets.
📄 Pre-print(arxiv): https://t.co/An5DsZbgrW
🌐 project page: https://t.co/tkvChOo0lB
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🧵(3/4) We generate several synthetic face datasets and evaluate them by training face recognition models and benchmarking trained models on real face recognition benchmark datasets. #ICML#ICML2025