Zobrazeno 1 - 10
of 43 969
pro vyhledávání: '"P. Sui"'
Quantization stands as a pivotal technique for large language model (LLM) serving, yet it poses significant challenges particularly in achieving effective low-bit quantization. The limited numerical mapping makes the quantized model produce a non-tri
Externí odkaz:
http://arxiv.org/abs/2411.07762
Autor:
Yee, Leanne Oon Hui, Fun, Siew Sui, Zin, Thit Sar, Aung, Zar Nie, Yap, Kian Meng, Teoh, Jiehan
In today's high-pressure and isolated society, the demand for emotional support has surged, necessitating innovative solutions. Socially Assistive Robots (SARs) offer a technological approach to providing emotional assistance by leveraging advanced r
Externí odkaz:
http://arxiv.org/abs/2411.05122
We consider a distributed detection problem within a wireless sensor network (WSN), where a substantial number of sensors cooperate to detect the existence of sparse stochastic signals. To achieve a trade-off between detection performance and system
Externí odkaz:
http://arxiv.org/abs/2411.03612
Autor:
Lu, Bing-Sui
We consider the Casimir-Polder interaction between a two-level atomic system and a Chern insulator for both the resonant and nonresonant channels. For a right circularly polarized excited atomic state near a Chern insulator with a negative Chern numb
Externí odkaz:
http://arxiv.org/abs/2411.01934
Autor:
Peng, Tianhao, Li, Yuchen, Li, Xuhong, Bian, Jiang, Xie, Zeke, Sui, Ning, Mumtaz, Shahid, Xu, Yanwu, Kong, Linghe, Xiong, Haoyi
Recent advancements in computational chemistry have leveraged the power of trans-former-based language models, such as MoLFormer, pre-trained using a vast amount of simplified molecular-input line-entry system (SMILES) sequences, to understand and pr
Externí odkaz:
http://arxiv.org/abs/2411.01401
Autor:
Yang, Cheng, Sui, Yang, Xiao, Jinqi, Huang, Lingyi, Gong, Yu, Duan, Yuanlin, Jia, Wenqi, Yin, Miao, Cheng, Yu, Yuan, Bo
The emergence of Mixture of Experts (MoE) LLMs has significantly advanced the development of language models. Compared to traditional LLMs, MoE LLMs outperform traditional LLMs by achieving higher performance with considerably fewer activated paramet
Externí odkaz:
http://arxiv.org/abs/2411.01016
Singing voice synthesis (SVS) aims to produce high-fidelity singing audio from music scores, requiring a detailed understanding of notes, pitch, and duration, unlike text-to-speech tasks. Although diffusion models have shown exceptional performance i
Externí odkaz:
http://arxiv.org/abs/2410.21641
Autor:
Binz, Marcel, Akata, Elif, Bethge, Matthias, Brändle, Franziska, Callaway, Fred, Coda-Forno, Julian, Dayan, Peter, Demircan, Can, Eckstein, Maria K., Éltető, Noémi, Griffiths, Thomas L., Haridi, Susanne, Jagadish, Akshay K., Ji-An, Li, Kipnis, Alexander, Kumar, Sreejan, Ludwig, Tobias, Mathony, Marvin, Mattar, Marcelo, Modirshanechi, Alireza, Nath, Surabhi S., Peterson, Joshua C., Rmus, Milena, Russek, Evan M., Saanum, Tankred, Scharfenberg, Natalia, Schubert, Johannes A., Buschoff, Luca M. Schulze, Singhi, Nishad, Sui, Xin, Thalmann, Mirko, Theis, Fabian, Truong, Vuong, Udandarao, Vishaal, Voudouris, Konstantinos, Wilson, Robert, Witte, Kristin, Wu, Shuchen, Wulff, Dirk, Xiong, Huadong, Schulz, Eric
Establishing a unified theory of cognition has been a major goal of psychology. While there have been previous attempts to instantiate such theories by building computational models, we currently do not have one model that captures the human mind in
Externí odkaz:
http://arxiv.org/abs/2410.20268
With the rapid development of natural language processing technology, large language models have demonstrated exceptional performance in various application scenarios. However, training these models requires significant computational resources and da
Externí odkaz:
http://arxiv.org/abs/2410.19130
In this work, we investigate the sampling and reconstruction of spectrally $s$-sparse bandlimited graph signals governed by heat diffusion processes. We propose a random space-time sampling regime, referred to as {randomized} dynamical sampling, wher
Externí odkaz:
http://arxiv.org/abs/2410.18005