Search Results for author: Yuxin Guo

Found 9 papers, 3 papers with code

CoReS: Orchestrating the Dance of Reasoning and Segmentation

no code implementations8 Apr 2024 Xiaoyi Bao, Siyang Sun, Shuailei Ma, Kecheng Zheng, Yuxin Guo, Guosheng Zhao, Yun Zheng, Xingang Wang

We believe that the act of reasoning segmentation should mirror the cognitive stages of human visual search, where each step is a progressive refinement of thought toward the final object.


Cross Pseudo-Labeling for Semi-Supervised Audio-Visual Source Localization

no code implementations5 Mar 2024 Yuxin Guo, Shijie Ma, Yuhao Zhao, Hu Su, Wei Zou

Audio-Visual Source Localization (AVSL) is the task of identifying specific sounding objects in the scene given audio cues.

Pseudo Label

Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model

no code implementations18 Dec 2023 Shuailei Ma, Chen-Wei Xie, Ying WEI, Siyang Sun, Jiaqi Fan, Xiaoyi Bao, Yuxin Guo, Yun Zheng

In this paper, we conduct a direct analysis of the multi-modal prompts by asking the following questions: $(i)$ How do the learned multi-modal prompts improve the recognition performance?

Language Modelling

ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation

no code implementations26 Oct 2023 Zi Lin, Zihan Wang, Yongqi Tong, Yangkun Wang, Yuxin Guo, Yujia Wang, Jingbo Shang

This benchmark contains the rich, nuanced phenomena that can be tricky for current toxicity detection models to identify, revealing a significant domain difference compared to social media content.


Data-centric Graph Learning: A Survey

no code implementations8 Oct 2023 Yuxin Guo, Deyu Bo, Cheng Yang, Zhiyuan Lu, Zhongjian Zhang, Jixi Liu, Yufei Peng, Chuan Shi

Recently, instead of designing more complex neural architectures as model-centric approaches, the attention of AI community has shifted to data-centric ones, which focuses on better processing data to strengthen the ability of neural models.

Graph Learning

TransPimLib: A Library for Efficient Transcendental Functions on Processing-in-Memory Systems

1 code implementation3 Apr 2023 Maurus Item, Juan Gómez-Luna, Yuxin Guo, Geraldo F. Oliveira, Mohammad Sadrosadati, Onur Mutlu

In order to provide support for transcendental (and other hard-to-calculate) functions in general-purpose PIM systems, we present \emph{TransPimLib}, a library that provides CORDIC-based and LUT-based methods for trigonometric functions, hyperbolic functions, exponentiation, logarithm, square root, etc.

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