68 citations · 125 across the 11 of their papers we have counts for
12 papers
Injecting Universal Jailbreak Backdoors into LLMs in Minutes
Zhuowei Chen, Qiannan Zhang, Shichao Pei
Jailbreak backdoor attacks on LLMs have garnered attention for their effectiveness and stealth. However, existing methods rely on the crafting of poisoned datasets and the time-con…
Zero-Shot Relational Learning for Multimodal Knowledge Graphs
Rui Cai, Shichao Pei, Xiangliang Zhang
Relational learning is an essential task in the domain of knowledge representation, particularly in knowledge graph completion (KGC). While relational learning in traditional singl…
Large Language Model based Multi-Agents: A Survey of Progress and Challenges
Taicheng Guo, Xiuying Chen, Yaqi Wang +5
Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as a…
ReactionTeam: Teaming Experts for Divergent Thinking Beyond Typical Reaction Patterns
Taicheng Guo, Changsheng Ma, Xiuying Chen +6
Reaction prediction, a critical task in synthetic chemistry, is to predict the outcome of a reaction based on given reactants. Generative models like Transformer have typically bee…
LogicRec: Recommendation with Users' Logical Requirements
Zhenwei Tang, Griffin Floto, Armin Toroghi +3
Users may demand recommendations with highly personalized requirements involving logical operations, e.g., the intersection of two requirements, where such requirements naturally f…
Knowledge Distillation on Graphs: A Survey
Yijun Tian, Shichao Pei, Xiangliang Zhang +2
Graph Neural Networks (GNNs) have attracted tremendous attention by demonstrating their capability to handle graph data. However, they are difficult to be deployed in resource-limi…
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Zhenwei Tang, Shichao Pei, Zhao Zhang +4
Most real-world knowledge graphs (KG) are far from complete and comprehensive. This problem has motivated efforts in predicting the most plausible missing facts to complete a given…
TAR: Neural Logical Reasoning across TBox and ABox
Zhenwei Tang, Shichao Pei, Xi Peng +3
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been developed to provide rich knowledge about various domains. An ontology consists of an ABox, i.e., assertion…
A Generic Knowledge Based Medical Diagnosis Expert System
Xin Huang, Xuejiao Tang, Wenbin Zhang +6
In this paper, we design and implement a generic medical knowledge based system (MKBS) for identifying diseases from several symptoms. In this system, some important aspects like k…
Scientific Dataset Discovery via Topic-level Recommendation
Basmah Altaf, Shichao Pei, Xiangliang Zhang
Data intensive research requires the support of appropriate datasets. However, it is often time-consuming to discover usable datasets matching a specific research topic. We formula…
SAIL: Self-Augmented Graph Contrastive Learning
Lu Yu, Shichao Pei, Lizhong Ding +4
This paper studies learning node representations with graph neural networks (GNNs) for unsupervised scenario. Specifically, we derive a theoretical analysis and provide an empirica…
Addressing Class-Imbalance Problem in Personalized Ranking
Lu Yu, Shichao Pei, Chuxu Zhang +4
Pairwise ranking models have been widely used to address recommendation problems. The basic idea is to learn the rank of users' preferred items through separating items into \emph{…