22 citations · 89 across the 36 of their papers we have counts for
6 papers · 1 filter
Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models
Shuyang Hao, Bryan Hooi, Jun Liu +3
Despite inheriting security measures from underlying language models, Vision-Language Models (VLMs) may still be vulnerable to safety alignment issues. Through empirical analysis,…
DRS: Deep Question Reformulation With Structured Output
Zhecheng Li, Yiwei Wang, Bryan Hooi +3
Question answering represents a core capability of large language models (LLMs). However, when individuals encounter unfamiliar knowledge in texts, they often formulate questions t…
Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization
Zhecheng Li, Yiwei Wang, Bryan Hooi +4
Cross-lingual summarization (CLS) aims to generate a summary for the source text in a different target language. Currently, instruction-tuned large language models (LLMs) excel at…
Vulnerability of LLMs to Vertically Aligned Text Manipulations
Zhecheng Li, Yiwei Wang, Bryan Hooi +4
Vertical text input is commonly encountered in various real-world applications, such as mathematical computations and word-based Sudoku puzzles. While current large language models…
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
Cheng Wang, Yiwei Wang, Bryan Hooi +3
The training data in large language models is key to their success, but it also presents privacy and security risks, as it may contain sensitive information. Detecting pre-training…
UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting
Juncheng Liu, Chenghao Liu, Gerald Woo +4
Transformer-based models have emerged as powerful tools for multivariate time series forecasting (MTSF). However, existing Transformer models often fall short of capturing both int…