Zobrazeno 1 - 10
of 29 300
pro vyhledávání: '"Chen Chun-An"'
Autor:
Chen, Chun, Shen, Rong-Feng
The radiation reprocessing model, in which an optically-thick outflow absorbs the high-energy emission from a central source and re-emits in longer wavelengths, has been frequently invoked to explain some optically bright transients, such as fast blu
Externí odkaz:
http://arxiv.org/abs/2411.18985
Despite the outstanding performance of Large language models (LLMs) in diverse tasks, they are vulnerable to jailbreak attacks, wherein adversarial prompts are crafted to bypass their security mechanisms and elicit unexpected responses.Although jailb
Externí odkaz:
http://arxiv.org/abs/2411.11114
LLM hallucination, where LLMs occasionally generate unfaithful text, poses significant challenges for their practical applications. Most existing detection methods rely on external knowledge, LLM fine-tuning, or hallucination-labeled datasets, and th
Externí odkaz:
http://arxiv.org/abs/2411.09689
Autor:
Huang, Chien-yu, Chen, Wei-Chih, Yang, Shu-wen, Liu, Andy T., Li, Chen-An, Lin, Yu-Xiang, Tseng, Wei-Cheng, Diwan, Anuj, Shih, Yi-Jen, Shi, Jiatong, Chen, William, Chen, Xuanjun, Hsiao, Chi-Yuan, Peng, Puyuan, Wang, Shih-Heng, Kuan, Chun-Yi, Lu, Ke-Han, Chang, Kai-Wei, Yang, Chih-Kai, Ritter-Gutierrez, Fabian, Chuang, Ming To, Huang, Kuan-Po, Arora, Siddhant, Lin, You-Kuan, Yeo, Eunjung, Chang, Kalvin, Chien, Chung-Ming, Choi, Kwanghee, Hsieh, Cheng-Hsiu, Lin, Yi-Cheng, Yu, Chee-En, Chiu, I-Hsiang, Guimarães, Heitor R., Han, Jionghao, Lin, Tzu-Quan, Lin, Tzu-Yuan, Chang, Homu, Chang, Ting-Wu, Chen, Chun Wei, Chen, Shou-Jen, Chen, Yu-Hua, Cheng, Hsi-Chun, Dhawan, Kunal, Fang, Jia-Lin, Fang, Shi-Xin, Chiang, Kuan-Yu Fang, Fu, Chi An, Hsiao, Hsien-Fu, Hsu, Ching Yu, Huang, Shao-Syuan, Wei, Lee Chen, Lin, Hsi-Che, Lin, Hsuan-Hao, Lin, Hsuan-Ting, Lin, Jian-Ren, Liu, Ting-Chun, Lu, Li-Chun, Pai, Tsung-Min, Pasad, Ankita, Kuan, Shih-Yun Shan, Shon, Suwon, Tang, Yuxun, Tsai, Yun-Shao, Wei, Jui-Chiang, Wei, Tzu-Chieh, Wu, Chengxi, Wu, Dien-Ruei, Yang, Chao-Han Huck, Yang, Chieh-Chi, Yip, Jia Qi, Yuan, Shao-Xiang, Noroozi, Vahid, Chen, Zhehuai, Wu, Haibin, Livescu, Karen, Harwath, David, Watanabe, Shinji, Lee, Hung-yi
Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spoken language model that comprehends a wide range of natural language i
Externí odkaz:
http://arxiv.org/abs/2411.05361
Embeddings have become a cornerstone in the functionality of large language models (LLMs) due to their ability to transform text data into rich, dense numerical representations that capture semantic and syntactic properties. These embedding vector da
Externí odkaz:
http://arxiv.org/abs/2411.05034
Autor:
Yang, Weiqin, Chen, Jiawei, Xin, Xin, Zhou, Sheng, Hu, Binbin, Feng, Yan, Chen, Chun, Wang, Can
Softmax Loss (SL) is widely applied in recommender systems (RS) and has demonstrated effectiveness. This work analyzes SL from a pairwise perspective, revealing two significant limitations: 1) the relationship between SL and conventional ranking metr
Externí odkaz:
http://arxiv.org/abs/2411.00163
Autor:
Rothe, Stefan, Wisal, Kabish, Chen, Chun-Wei, Ercan, Mert, Jesacher, Alexander, Stone, A. Douglas, Cao, Hui
Multimode fibers provide a promising platform for realizing high-power laser amplifiers with suppressed nonlinearities and instabilities. The potential degradation of optical beam quality has been a major concern for highly multimode fiber amplifiers
Externí odkaz:
http://arxiv.org/abs/2410.23361
Autor:
Wang, Zhe, Zhao, Tianjian, Zhang, Zhen, Chen, Jiawei, Zhou, Sheng, Feng, Yan, Chen, Chun, Wang, Can
Dynamic Graph Neural Networks (DyGNNs) have garnered increasing research attention for learning representations on evolving graphs. Despite their effectiveness, the limited expressive power of existing DyGNNs hinders them from capturing important evo
Externí odkaz:
http://arxiv.org/abs/2410.01367
The effectiveness of watermark algorithms in AI-generated text identification has garnered significant attention. Concurrently, an increasing number of watermark algorithms have been proposed to enhance the robustness against various watermark attack
Externí odkaz:
http://arxiv.org/abs/2409.19708
Diffusion-based generative models have demonstrated their powerful performance across various tasks, but this comes at a cost of the slow sampling speed. To achieve both efficient and high-quality synthesis, various distillation-based accelerated sam
Externí odkaz:
http://arxiv.org/abs/2409.19681