14 citations · 19 across the 8 of their papers we have counts for
9 papers
Pre-Trained Model Recommendation for Downstream Fine-tuning
Jiameng Bai, Sai Wu, Jie Song +2
As a fundamental problem in transfer learning, model selection aims to rank off-the-shelf pre-trained models and select the most suitable one for the new target task. Existing mode…
ModelGiF: Gradient Fields for Model Functional Distance
Jie Song, Zhengqi Xu, Sai Wu +2
The last decade has witnessed the success of deep learning and the surge of publicly released trained models, which necessitates the quantification of the model functional distance…
Towards Cross-Table Masked Pretraining for Web Data Mining
Chao Ye, Guoshan Lu, Haobo Wang +4
Tabular data pervades the landscape of the World Wide Web, playing a foundational role in the digital architecture that underpins online information. Given the recent influence of…
Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility
Wentao Ye, Mingfeng Ou, Tianyi Li +8
The recent popularity of large language models (LLMs) has brought a significant impact to boundless fields, particularly through their open-ended ecosystem such as the APIs, open-s…
Controllable Textual Inversion for Personalized Text-to-Image Generation
Jianan Yang, Haobo Wang, Yanming Zhang +4
The recent large-scale generative modeling has attained unprecedented performance especially in producing high-fidelity images driven by text prompts. Text inversion (TI), alongsid…
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting
Yuchen Liu, Chen Chen, Lingjuan Lyu +3
Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and…
Comparison Knowledge Translation for Generalizable Image Classification
Zunlei Feng, Tian Qiu, Sai Wu +4
Deep learning has recently achieved remarkable performance in image classification tasks, which depends heavily on massive annotation. However, the classification mechanism of exis…
Towards Unifying the Label Space for Aspect- and Sentence-based Sentiment Analysis
Yiming Zhang, Min Zhang, Sai Wu +1
The aspect-based sentiment analysis (ABSA) is a fine-grained task that aims to determine the sentiment polarity towards targeted aspect terms occurring in the sentence. The develop…
Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers
Zunlei Feng, Jiacong Hu, Sai Wu +3
Recently, Convolutional Neural Network (CNN) has achieved excellent performance in the classification task. It is widely known that CNN is deemed as a 'black-box', which is hard fo…