Zobrazeno 1 - 10
of 18 256
pro vyhledávání: '"Mian, P"'
The widespread availability of multimodal generative models has sparked critical discussions on their fairness, reliability, and potential for misuse. While text-to-image models can produce high-fidelity, user-guided images, they also exhibit unpredi
Externí odkaz:
http://arxiv.org/abs/2411.13981
Training multimodal generative models on large, uncurated datasets can result in users being exposed to harmful, unsafe and controversial or culturally-inappropriate outputs. While model editing has been proposed to remove or filter undesirable conce
Externí odkaz:
http://arxiv.org/abs/2411.13982
Lossy compression methods rely on an autoencoder to transform a point cloud into latent points for storage, leaving the inherent redundancy of latent representations unexplored. To reduce redundancy in latent points, we propose a sparse priors guided
Externí odkaz:
http://arxiv.org/abs/2411.13860
Autor:
Deng, Andong, Chen, Tongjia, Yu, Shoubin, Yang, Taojiannan, Spencer, Lincoln, Tian, Yapeng, Mian, Ajmal Saeed, Bansal, Mohit, Chen, Chen
In this paper, we introduce Motion-Grounded Video Reasoning, a new motion understanding task that requires generating visual answers (video segmentation masks) according to the input question, and hence needs implicit spatiotemporal reasoning and gro
Externí odkaz:
http://arxiv.org/abs/2411.09921
Autor:
Song, Yunxiang, Hu, Yaowen, Zhu, Xinrui, Powell, Keith, Magalhães, Letícia, Ye, Fan, Warner, Hana, Lu, Shengyuan, Li, Xudong, Renaud, Dylan, Lippok, Norman, Zhu, Di, Vakoc, Benjamin, Zhang, Mian, Sinclair, Neil, Lončar, Marko
The rapid growth in artificial intelligence and modern communication systems demands innovative solutions for increased computational power and advanced signaling capabilities. Integrated photonics, leveraging the analog nature of electromagnetic wav
Externí odkaz:
http://arxiv.org/abs/2411.04395
Autor:
Hu, Yaowen, Song, Yunxiang, Zhu, Xinrui, Guo, Xiangwen, Lu, Shengyuan, Zhang, Qihang, He, Lingyan, Franken, C. A. A., Powell, Keith, Warner, Hana, Assumpcao, Daniel, Renaud, Dylan, Wang, Ying, Magalhães, Letícia, Rosborough, Victoria, Shams-Ansari, Amirhassan, Li, Xudong, Cheng, Rebecca, Luke, Kevin, Yang, Kiyoul, Barbastathis, George, Zhang, Mian, Zhu, Di, Johansson, Leif, Beling, Andreas, Sinclair, Neil, Loncar, Marko
Here we show a photonic computing accelerator utilizing a system-level thin-film lithium niobate circuit which overcomes this limitation. Leveraging the strong electro-optic (Pockels) effect and the scalability of this platform, we demonstrate photon
Externí odkaz:
http://arxiv.org/abs/2411.02734
We introduce Referring Human Pose and Mask Estimation (R-HPM) in the wild, where either a text or positional prompt specifies the person of interest in an image. This new task holds significant potential for human-centric applications such as assisti
Externí odkaz:
http://arxiv.org/abs/2410.20508
Autor:
Fang, Qian, Wang, Liming, Chang, Kai, Yang, Hongxin, Yan, Pu, Cao, Kecheng, Li, Mian, Chai, Zhifang, Huang, Qing
Two-dimensional (2D) magnetic semiconductors are a key focus in developing next-generation information storage technologies. MXenes, as emerging 2D early transition metal carbides and nitrides, offer versatile compositions and tunable chemical struct
Externí odkaz:
http://arxiv.org/abs/2410.18337
Autor:
Zhang, Mian, Yang, Xianjun, Zhang, Xinlu, Labrum, Travis, Chiu, Jamie C., Eack, Shaun M., Fang, Fei, Wang, William Yang, Chen, Zhiyu Zoey
There is a significant gap between patient needs and available mental health support today. In this paper, we aim to thoroughly examine the potential of using Large Language Models (LLMs) to assist professional psychotherapy. To this end, we propose
Externí odkaz:
http://arxiv.org/abs/2410.13218
Large Language Models (LLMs), such as GPT-4 and BERT, have rapidly gained traction in natural language processing (NLP) and are now integral to financial decision-making. However, their deployment introduces critical challenges, particularly in perpe
Externí odkaz:
http://arxiv.org/abs/2410.19775