8 citations · 18 across the 15 of their papers we have counts for
5 papers · 1 filter
Bias at the End of the Score
Salma Abdel Magid, Grace Guo, Esin Tureci +4
Reward models (RMs) are inherently non-neutral value functions designed and trained to encode specific objectives, such as human preferences or text-image alignment. RMs have becom…
They're All Doctors: Synthesizing Diverse Counterfactuals to Mitigate Associative Bias
Salma Abdel Magid, Jui-Hsien Wang, Kushal Kafle +1
Vision Language Models (VLMs) such as CLIP are powerful models; however they can exhibit unwanted biases, making them less safe when deployed directly in applications such as text-…
Unraveling the Temporal Dynamics of the Unet in Diffusion Models
Vidya Prasad, Chen Zhu-Tian, Anna Vilanova +3
Diffusion models have garnered significant attention since they can effectively learn complex multivariate Gaussian distributions, resulting in diverse, high-quality outcomes. They…
LangSplat: 3D Language Gaussian Splatting
Minghan Qin, Wanhua Li, Jiawei Zhou +2
Humans live in a 3D world and commonly use natural language to interact with a 3D scene. Modeling a 3D language field to support open-ended language queries in 3D has gained increa…
Can Machines Imitate Humans? Integrative Turing-like tests for Language and Vision Demonstrate a Narrowing Gap
Mengmi Zhang, Elisa Pavarino, Xiao Liu +20
As AI becomes increasingly embedded in daily life, ascertaining whether an agent is human is critical. We systematically benchmark AI's ability to imitate humans in three language…