Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Chang, Zhiyuan"'
Text-to-Image Diffusion Models (T2I DMs) have garnered significant attention for their ability to generate high-quality images from textual descriptions. However, these models often produce images that do not fully align with the input prompts, resul
Externí odkaz:
http://arxiv.org/abs/2406.16272
Visual entailment (VE) is a multimodal reasoning task consisting of image-sentence pairs whereby a promise is defined by an image, and a hypothesis is described by a sentence. The goal is to predict whether the image semantically entails the sentence
Externí odkaz:
http://arxiv.org/abs/2403.02581
Due to the advantages of fusing information from various modalities, multimodal learning is gaining increasing attention. Being a fundamental task of multimodal learning, Visual Grounding (VG), aims to locate objects in images through natural languag
Externí odkaz:
http://arxiv.org/abs/2403.01118
Publikováno v:
The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)
With the development of LLMs, the security threats of LLMs are getting more and more attention. Numerous jailbreak attacks have been proposed to assess the security defense of LLMs. Current jailbreak attacks primarily utilize scenario camouflage tech
Externí odkaz:
http://arxiv.org/abs/2402.09091
Natural language (NL) documentation is the bridge between software managers and testers, and NL test cases are prevalent in system-level testing and other quality assurance activities. Due to reasons such as requirements redundancy, parallel testing,
Externí odkaz:
http://arxiv.org/abs/2210.01661
Publikováno v:
In Materialia May 2024 34
Publikováno v:
In International Journal of Hydrogen Energy 3 April 2024 61:1060-1070
Publikováno v:
In Applied Thermal Engineering 1 March 2024 240
Autor:
Yu, Cansheng, Sun, Lirong, Xi, Han, Liu, Yi, Li, Yunjie, Kang, Jian, Wang, Hesong, Chang, Zhiyuan
Publikováno v:
In Journal of Materials Research and Technology January-February 2024 28:533-545
Publikováno v:
In Energy 1 November 2023 282