Zobrazeno 1 - 10
of 6 817
pro vyhledávání: '"Jiang, Xue"'
Autor:
Frikha, Ahmed, Walha, Nassim, Mendes, Ricardo, Nakka, Krishna Kanth, Jiang, Xue, Zhou, Xuebing
This work addresses the timely yet underexplored problem of performing inference and finetuning of a proprietary LLM owned by a model provider entity on the confidential/private data of another data owner entity, in a way that ensures the confidentia
Externí odkaz:
http://arxiv.org/abs/2407.02960
Autor:
Frikha, Ahmed, Walha, Nassim, Nakka, Krishna Kanth, Mendes, Ricardo, Jiang, Xue, Zhou, Xuebing
In this work, we address the problem of text anonymization where the goal is to prevent adversaries from correctly inferring private attributes of the author, while keeping the text utility, i.e., meaning and semantics. We propose IncogniText, a tech
Externí odkaz:
http://arxiv.org/abs/2407.02956
The latest and most impactful advances in large models stem from their increased size. Unfortunately, this translates into an improved memorization capacity, raising data privacy concerns. Specifically, it has been shown that models can output person
Externí odkaz:
http://arxiv.org/abs/2407.02943
Vision-Language Foundation Models (VLFMs) have made remarkable progress on various multimodal tasks, such as image captioning, image-text retrieval, visual question answering, and visual grounding. However, most methods rely on training with general
Externí odkaz:
http://arxiv.org/abs/2406.09385
Autor:
Yu, Qingzheng, Fang, Taotao, Xu, Cong Kevin, Feng, Shuai, Feng, Siyi, Gao, Yu, Jiang, Xue-Jian, Lisenfeld, Ute
We present a study of the molecular gas in early-mid stage major-mergers, with a sample of 43 major-merger galaxy pairs selected from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey and a control sample of 195 isolated galaxies
Externí odkaz:
http://arxiv.org/abs/2404.18999
Autor:
Mou, Yicheng, Chen, Haonan, Liu, Jiaqi, Lan, Qing, Wang, Jiayu, Zhang, Chuanxin, Wang, Yuxiang, Gu, Jiaming, Zhao, Tuoyu, Jiang, Xue, Shi, Wu, Zhang, Cheng
Transport probes the motion of quasiparticles in response to external excitations. Apart from the well-known electric and thermoelectric transport, acoustoelectric transport induced by traveling acoustic waves has been rarely explored. Here, by adopt
Externí odkaz:
http://arxiv.org/abs/2403.20248
Out-of-distribution (OOD) detection aims at identifying samples from unknown classes, playing a crucial role in trustworthy models against errors on unexpected inputs. Extensive research has been dedicated to exploring OOD detection in the vision mod
Externí odkaz:
http://arxiv.org/abs/2403.20078
Although Large Language Models (LLMs) have made significant progress in code generation, they still struggle with code generation tasks in specific scenarios. These scenarios usually necessitate the adaptation of LLMs to fulfill specific needs, but t
Externí odkaz:
http://arxiv.org/abs/2403.00046
Recent statements about the impressive capabilities of large language models (LLMs) are usually supported by evaluating on open-access benchmarks. Considering the vast size and wide-ranging sources of LLMs' training data, it could explicitly or impli
Externí odkaz:
http://arxiv.org/abs/2402.15938
In this work, a tensor completion problem is studied, which aims to perfectly recover the tensor from partial observations. Existing theoretical guarantee requires the involved transform to be orthogonal, which hinders its applications. In this paper
Externí odkaz:
http://arxiv.org/abs/2402.03468