Publications (6)
From Insight to Exploit: Leveraging LLM Collaboration for Adaptive Adversarial Text Generation
Najrin Sultana, Md Rafi Ur Rashid, Kang Gu +1
LLMs can provide substantial zero-shot performance on diverse tasks using a simple task prompt, eliminating the need for training or fine-tuning. However, when applying these model…
DocGraphLM: Documental Graph Language Model for Information Extraction
Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh +2
Advances in Visually Rich Document Understanding (VrDU) have enabled information extraction and question answering over documents with complex layouts. Two tropes of architectures…
Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Shuangjie Xu, Yu Cheng, Kang Gu +3
Person Re-Identification (person re-id) is a crucial task as its applications in visual surveillance and human-computer interaction. In this work, we present a novel joint Spatial…
Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models
Kang Gu, Md Rafi Ur Rashid, Najrin Sultana +1
With the rapid development of Large Language Models (LLMs), we have witnessed intense competition among the major LLM products like ChatGPT, LLaMa, and Gemini. However, various iss…
Feature Selection for Multivariate Time Series via Network Pruning
Kang Gu, Soroush Vosoughi, Temiloluwa Prioleau
In recent years, there has been an ever increasing amount of multivariate time series (MTS) data in various domains, typically generated by a large family of sensors such as wearab…
Gradient-Free Privacy Leakage in Federated Language Models through Selective Weight Tampering
Md Rafi Ur Rashid, Vishnu Asutosh Dasu, Kang Gu +2
Federated learning (FL) has become a key component in various language modeling applications such as machine translation, next-word prediction, and medical record analysis. These a…