Zobrazeno 1 - 10
of 52 798
pro vyhledávání: '"An, Yixin"'
Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These requiremen
Externí odkaz:
http://arxiv.org/abs/2410.03187
Autor:
Ruan, Charlie F., Qin, Yucheng, Zhou, Xun, Lai, Ruihang, Jin, Hongyi, Dong, Yixin, Hou, Bohan, Yu, Meng-Shiun, Zhai, Yiyan, Agarwal, Sudeep, Cao, Hangrui, Feng, Siyuan, Chen, Tianqi
Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-grade GPUs and cloud-based inference, the recent emergence of smaller open-source models and increasingly power
Externí odkaz:
http://arxiv.org/abs/2412.15803
The integration of multi-omic data is pivotal for understanding complex diseases, but its high dimensionality and noise present significant challenges. Graph Neural Networks (GNNs) offer a robust framework for analyzing large-scale signaling pathways
Externí odkaz:
http://arxiv.org/abs/2412.15790
Autor:
He, Tao, Liao, Lizi, Cao, Yixin, Liu, Yuanxing, Sun, Yiheng, Chen, Zerui, Liu, Ming, Qin, Bing
Recent advancements in proactive dialogues have garnered significant attention, particularly for more complex objectives (e.g. emotion support and persuasion). Unlike traditional task-oriented dialogues, proactive dialogues demand advanced policy pla
Externí odkaz:
http://arxiv.org/abs/2412.14584
Autor:
Zhao, Zihang, Li, Wanlin, Li, Yuyang, Liu, Tengyu, Li, Boren, Wang, Meng, Du, Kai, Liu, Hangxin, Zhu, Yixin, Wang, Qining, Althoefer, Kaspar, Zhu, Song-Chun
Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite significant advances in replicating human hand kinematics and control algorithms, robotic systems still struggle
Externí odkaz:
http://arxiv.org/abs/2412.14482
Autor:
Geng, Xiwen, Zhao, Suyun, Yu, Yixin, Peng, Borui, Du, Pan, Chen, Hong, Li, Cuiping, Wang, Mengdie
Clustering traditionally aims to reveal a natural grouping structure within unlabeled data. However, this structure may not always align with users' preferences. In this paper, we propose a personalized clustering method that explicitly performs targ
Externí odkaz:
http://arxiv.org/abs/2412.13690
Autor:
Tang, Wei, Cao, Yixin, Deng, Yang, Ying, Jiahao, Wang, Bo, Yang, Yizhe, Zhao, Yuyue, Zhang, Qi, Huang, Xuanjing, Jiang, Yugang, Liao, Yong
Knowledge utilization is a critical aspect of LLMs, and understanding how they adapt to evolving knowledge is essential for their effective deployment. However, existing benchmarks are predominantly static, failing to capture the evolving nature of L
Externí odkaz:
http://arxiv.org/abs/2412.13582
This paper introduces posterior mean matching (PMM), a new method for generative modeling that is grounded in Bayesian inference. PMM uses conjugate pairs of distributions to model complex data of various modalities like images and text, offering a f
Externí odkaz:
http://arxiv.org/abs/2412.13286
Publikováno v:
CIKM(2024) 4718-4725
With the rapid advancement of pre-trained large language models (LLMs), recent endeavors have leveraged the capabilities of LLMs in relevance modeling, resulting in enhanced performance. This is usually done through the process of fine-tuning LLMs on
Externí odkaz:
http://arxiv.org/abs/2412.12504
Optimal control problems (OCPs) involve finding a control function for a dynamical system such that a cost functional is optimized. It is central to physical systems in both academia and industry. In this paper, we propose a novel instance-solution c
Externí odkaz:
http://arxiv.org/abs/2412.12469