Zobrazeno 1 - 10
of 14 432
pro vyhledávání: '"ChENg, WEN"'
ESPERANTO: Evaluating Synthesized Phrases to Enhance Robustness in AI Detection for Text Origination
Autor:
Ayoobi, Navid, Knab, Lily, Cheng, Wen, Pantoja, David, Alikhani, Hamidreza, Flamant, Sylvain, Kim, Jin, Mukherjee, Arjun
While large language models (LLMs) exhibit significant utility across various domains, they simultaneously are susceptible to exploitation for unethical purposes, including academic misconduct and dissemination of misinformation. Consequently, AI-gen
Externí odkaz:
http://arxiv.org/abs/2409.14285
Autor:
Yeo, Jeong Hun, Kim, Chae Won, Kim, Hyunjun, Rha, Hyeongseop, Han, Seunghee, Cheng, Wen-Huang, Ro, Yong Man
Lip reading aims to predict spoken language by analyzing lip movements. Despite advancements in lip reading technologies, performance degrades when models are applied to unseen speakers due to their sensitivity to variations in visual information suc
Externí odkaz:
http://arxiv.org/abs/2409.00986
The rapid development of large language models (LLMs) has significantly advanced code completion capabilities, giving rise to a new generation of LLM-based Code Completion Tools (LCCTs). Unlike general-purpose LLMs, these tools possess unique workflo
Externí odkaz:
http://arxiv.org/abs/2408.11006
Autor:
Jiang-Lin, Jian-Yu, Huang, Kang-Yang, Lo, Ling, Huang, Yi-Ning, Lin, Terence, Wu, Jhih-Ciang, Shuai, Hong-Han, Cheng, Wen-Huang
Diffusion models revolutionize image generation by leveraging natural language to guide the creation of multimedia content. Despite significant advancements in such generative models, challenges persist in depicting detailed human-object interactions
Externí odkaz:
http://arxiv.org/abs/2407.17911
Autor:
Yao, Yi, Hsu, Chan-Feng, Lin, Jhe-Hao, Xie, Hongxia, Lin, Terence, Huang, Yi-Ning, Shuai, Hong-Han, Cheng, Wen-Huang
In spite of recent advancements in text-to-image generation, limitations persist in handling complex and imaginative prompts due to the restricted diversity and complexity of training data. This work explores how diffusion models can generate images
Externí odkaz:
http://arxiv.org/abs/2407.12579
Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range. At present, cameras used
Externí odkaz:
http://arxiv.org/abs/2407.04277
Publikováno v:
J. Mech. Phys. Solids, 193(105842), 2024
Extremal elastic materials here refer to a specific class of elastic materials whose elastic matrices exhibit one or more zero eigenvalues, resulting in soft deformation modes that, in principle, cost no energy. They can be approximated through artif
Externí odkaz:
http://arxiv.org/abs/2406.07462
Autor:
Liu, Hou-I, Tseng, Yu-Wen, Chang, Kai-Cheng, Wang, Pin-Jyun, Shuai, Hong-Han, Cheng, Wen-Huang
Despite notable advancements in the field of computer vision, the precise detection of tiny objects continues to pose a significant challenge, largely owing to the minuscule pixel representation allocated to these objects in imagery data. This challe
Externí odkaz:
http://arxiv.org/abs/2406.05755
UAV tracking and pose estimation plays an imperative role in various UAV-related missions, such as formation control and anti-UAV measures. Accurately detecting and tracking UAVs in a 3D space remains a particularly challenging problem, as it require
Externí odkaz:
http://arxiv.org/abs/2405.16867
Autor:
Wu, Bo, Liu, Peiye, Cheng, Wen-Huang, Liu, Bei, Zeng, Zhaoyang, Wang, Jia, Huang, Qiushi, Luo, Jiebo
Social Media Popularity Prediction (SMPP) is a crucial task that involves automatically predicting future popularity values of online posts, leveraging vast amounts of multimodal data available on social media platforms. Studying and investigating so
Externí odkaz:
http://arxiv.org/abs/2405.10497