5 citations · 13 across the 8 of their papers we have counts for
8 papers
Semantic-Preserving Prompt Hijacking: A Black-Box Adversarial Attack on Auto-Prompt Optimization
Chong Zhang, Xiang Li, Jia Wang +3
LLMs increasingly integrate auto-suggestion optimization modules, enabling them to rewrite and display user input before generating the final response. While this design aims to en…
Multi-task Prompt Words Learning for Social Media Content Generation
Haochen Xue, Chong Zhang, Chengzhi Liu +2
The rapid development of the Internet has profoundly changed human life. Humans are increasingly expressing themselves and interacting with others on social media platforms. Howeve…
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
Wenyue Hua, Kaijie Zhu, Lingyao Li +7
This study intends to systematically disentangle pure logic reasoning and text understanding by investigating the contrast across abstract and contextualized logical problems from…
ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction
Mingyu Jin, Haochen Xue, Zhenting Wang +5
The prediction of protein-protein interactions (PPIs) is crucial for understanding biological functions and diseases. Previous machine learning approaches to PPI prediction mainly…
Goal-guided Generative Prompt Injection Attack on Large Language Models
Chong Zhang, Mingyu Jin, Qinkai Yu +3
Current large language models (LLMs) provide a strong foundation for large-scale user-oriented natural language tasks. A large number of users can easily inject adversarial text or…
Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning
Chong Zhang, Mingyu Jin, Qinkai Yu +3
Generalized zero-shot learning (GZSL) aims to recognize samples from both seen and unseen classes using only seen class samples for training. However, GZSL methods are prone to bia…
A Simple and Effective Baseline for Attentional Generative Adversarial Networks
Mingyu Jin, Chong Zhang, Qinkai Yu +3
Synthesising a text-to-image model of high-quality images by guiding the generative model through the Text description is an innovative and challenging task. In recent years, AttnG…
Image Blending Algorithm with Automatic Mask Generation
Haochen Xue, Mingyu Jin, Chong Zhang +3
In recent years, image blending has gained popularity for its ability to create visually stunning content. However, the current image blending algorithms mainly have the following…