Zobrazeno 1 - 10
of 152 737
pro vyhledávání: '"Ong AN"'
Autor:
Noravesh, Farshad, Haffari, Reza, Fang, Ong Huey, Soon, Layki, Rajalana, Sailaja, Pal, Arghya
Many models are proposed in the literature on biomedical event extraction(BEE). Some of them use the shortest dependency path(SDP) information to represent the argument classification task. There is an issue with this representation since even missin
Externí odkaz:
http://arxiv.org/abs/2501.01158
Autor:
Ong, J. M. Joel
Existing asteroseismic rotational measurements assume that stars rotate around a single axis. However, tidal torques from misaligned companions, or their possible engulfment, may bring the rotational axis of a star's envelope out of alignment with it
Externí odkaz:
http://arxiv.org/abs/2412.19451
Autor:
Ke, Yu He, Jin, Liyuan, Elangovan, Kabilan, Ong, Bryan Wen Xi, Oh, Chin Yang, Sim, Jacqueline, Loh, Kenny Wei-Tsen, Soh, Chai Rick, Cheng, Jonathan Ming Hua, Lee, Aaron Kwang Yang, Ting, Daniel Shu Wei, Liu, Nan, Abdullah, Hairil Rizal
Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based system integra
Externí odkaz:
http://arxiv.org/abs/2412.18096
In the era of increasing privacy concerns and demand for personalized experiences, traditional Reinforcement Learning with Human Feedback (RLHF) frameworks face significant challenges due to their reliance on centralized data. We introduce Federated
Externí odkaz:
http://arxiv.org/abs/2412.15538
Incorporating multi-modal features as side information has recently become a trend in recommender systems. To elucidate user-item preferences, recent studies focus on fusing modalities via concatenation, element-wise sum, or attention mechanisms. Des
Externí odkaz:
http://arxiv.org/abs/2412.14978
As AI systems are integrated into social networks, there are AI safety concerns that AI-generated content may dominate the web, e.g. in popularity or impact on beliefs. To understand such questions, this paper proposes the Digital Ecosystem of Belief
Externí odkaz:
http://arxiv.org/abs/2412.14500
We develop the framework of Indirect Query Bayesian Optimization (IQBO), a new class of Bayesian optimization problems where the integrated feedback is given via a conditional expectation of the unknown function $f$ to be optimized. The underlying co
Externí odkaz:
http://arxiv.org/abs/2412.13559
We introduce a version of probabilistic Kleene algebra with angelic nondeterminism and a corresponding class of automata. Our approach implements semantics via distributions over multisets in order to overcome theoretical barriers arising from the la
Externí odkaz:
http://arxiv.org/abs/2412.06754
Autor:
Xu, Qingshan, Cui, Jiequan, Yi, Xuanyu, Wang, Yuxuan, Zhou, Yuan, Ong, Yew-Soon, Zhang, Hanwang
3D Gaussian Splatting (3DGS) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magnitude of view-space positional gradients to grow Gaussians to reduce re
Externí odkaz:
http://arxiv.org/abs/2412.04826
This paper presents a novel approach for synthesizing control barrier functions (CBFs) from high relative degree safety constraints: Rectified CBFs (ReCBFs). We begin by discussing the limitations of existing High-Order CBF approaches and how these c
Externí odkaz:
http://arxiv.org/abs/2412.03708