Zobrazeno 1 - 10
of 810
pro vyhledávání: '"Wang, Xintong"'
Designing automated market makers (AMMs) for prediction markets on combinatorial securities over large outcome spaces poses significant computational challenges. Prior research has primarily focused on combinatorial prediction markets within specific
Externí odkaz:
http://arxiv.org/abs/2411.08972
Autor:
Hua, Wenyue, Liu, Ollie, Li, Lingyao, Amayuelas, Alfonso, Chen, Julie, Jiang, Lucas, Jin, Mingyu, Fan, Lizhou, Sun, Fei, Wang, William, Wang, Xintong, Zhang, Yongfeng
This paper investigates the rationality of large language models (LLMs) in strategic decision-making contexts, specifically within the framework of game theory. We evaluate several state-of-the-art LLMs across a spectrum of complete-information and i
Externí odkaz:
http://arxiv.org/abs/2411.05990
Despite their impressive capabilities, large language models (LLMs) often lack interpretability and can generate toxic content. While using LLMs as foundation models and applying semantic steering methods are widely practiced, we believe that efficie
Externí odkaz:
http://arxiv.org/abs/2410.17714
Autor:
Talvitie, Erin J., Shao, Zilei, Li, Huiying, Hu, Jinghan, Boerma, Jacob, Zhao, Rory, Wang, Xintong
In model-based reinforcement learning, simulated experiences from the learned model are often treated as equivalent to experience from the real environment. However, when the model is inaccurate, it can catastrophically interfere with policy learning
Externí odkaz:
http://arxiv.org/abs/2406.16006
Mispronunciation Detection and Diagnosis (MDD) systems, leveraging Automatic Speech Recognition (ASR), face two main challenges in Mandarin Chinese: 1) The two-stage models create an information gap between the phoneme or tone classification stage an
Externí odkaz:
http://arxiv.org/abs/2406.04595
Large Vision-Language Models (LVLMs) are increasingly adept at generating contextually detailed and coherent responses from visual inputs. However, their application in multimodal decision-making and open-ended generation is hindered by a notable rat
Externí odkaz:
http://arxiv.org/abs/2403.18715
Autor:
Wang, Xinzhou, Wang, Yikai, Ye, Junliang, Wang, Zhengyi, Sun, Fuchun, Liu, Pengkun, Wang, Ling, Sun, Kai, Wang, Xintong, He, Bin
Advances in 3D generation have facilitated sequential 3D model generation (a.k.a 4D generation), yet its application for animatable objects with large motion remains scarce. Our work proposes AnimatableDreamer, a text-to-4D generation framework capab
Externí odkaz:
http://arxiv.org/abs/2312.03795
Large Language Models (LLMs) have emerged as dominant foundational models in modern NLP. However, the understanding of their prediction processes and internal mechanisms, such as feed-forward networks (FFN) and multi-head self-attention (MHSA), remai
Externí odkaz:
http://arxiv.org/abs/2310.05216
It is challenging to build a multi-singer high-fidelity singing voice synthesis system with cross-lingual ability by only using monolingual singers in the training stage. In this paper, we propose CrossSinger, which is a cross-lingual singing voice s
Externí odkaz:
http://arxiv.org/abs/2309.12672
Designing efficient and high-accuracy numerical methods for complex dynamic incompressible magnetohydrodynamics (MHD) equations remains a challenging problem in various analysis and design tasks. This is mainly due to the nonlinear coupling of the ma
Externí odkaz:
http://arxiv.org/abs/2305.07940