233 citations · 264 across the 8 of their papers we have counts for
8 papers
GiFT: Gibbs Fine-Tuning for Code Generation
Haochen Li, Wanjin Feng, Xin Zhou +1
Training Large Language Models (LLMs) with synthetic data is a prevalent practice in code generation. A key approach is self-training, where LLMs are iteratively trained on self-ge…
LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarks
Tianyi Wang, Mengxiao Huang, Harry Cheng +2
Deepfake facial manipulation has garnered significant public attention due to its impacts on enhancing human experiences and posing privacy threats. Despite numerous passive algori…
Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation
Honglei Zhang, Haoxuan Li, Jundong Chen +6
Federated recommendation aims to collect global knowledge by aggregating local models from massive devices, to provide recommendations while ensuring privacy. Current methods mainl…
Enabling Patient-side Disease Prediction via the Integration of Patient Narratives
Zhixiang Su, Yinan Zhang, Jiazheng Jing +2
Disease prediction holds considerable significance in modern healthcare, because of its crucial role in facilitating early intervention and implementing effective prevention measur…
Are ID Embeddings Necessary? Whitening Pre-trained Text Embeddings for Effective Sequential Recommendation
Lingzi Zhang, Xin Zhou, Zhiwei Zeng +1
Recent sequential recommendation models have combined pre-trained text embeddings of items with item ID embeddings to achieve superior recommendation performance. Despite their eff…
Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey
Haochen Li, Jonathan Leung, Zhiqi Shen
Large Language Models (LLMs) have shown prominent performance in various downstream tasks and prompt engineering plays a pivotal role in optimizing LLMs' performance. This paper, n…
Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search
Haochen Li, Xin Zhou, Zhiqi Shen
In code search, the Generation-Augmented Retrieval (GAR) framework, which generates exemplar code snippets to augment queries, has emerged as a promising strategy to address the pr…
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation
Xin Zhou, Zhiqi Shen
Multimodal recommender systems utilizing multimodal features (e.g., images and textual descriptions) typically show better recommendation accuracy than general recommendation model…