9 citations · 19 across the 13 of their papers we have counts for
13 papers
HyperClaim: Fine-Grained Cross-Modal Hypergraph Reasoning for Video Misinformation Detection
Xiangbo Wang, Jiasheng Zhang, Xingtong Yu +2
Video misinformation detection is often approached through global multimodal fusion or free-form multimodal reasoning. Both paradigms can under-represent localized authenticity cue…
LitBench: A Graph-Centric Large Language Model Benchmarking Tool For Literature Tasks
Andreas Varvarigos, Ali Maatouk, Jiasheng Zhang +4
While large language models (LLMs) have become the de facto framework for literature-related tasks, they still struggle to function as domain-specific literature agents due to thei…
TKGB: A Comprehensive Benchmark for Temporal Knowledge Graph Forecasting
Zhang Jiasheng, Jiasheng Zhang, Zhengpin Li +9
Temporal knowledge graph (TKG) forecasting has advanced remarkably in recent years. Yet we found existing benchmarks inadvertently introduce a shortcut: For a subset of test querie…
Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
Bojian Hou, Xiaolong Liu, Xiaoyi Liu +26
Deriving predictable scaling laws that govern the relationship between model performance and computational investment is crucial for designing and allocating resources in massive-s…
NeuroPath: Neurobiology-Inspired Path Tracking and Reflection for Semantically Coherent Retrieval
Junchen Li, Rongzheng Wang, Yihong Huang +3
Retrieval-augmented generation (RAG) greatly enhances large language models (LLMs) performance in knowledge-intensive tasks. However, naive RAG methods struggle with multi-hop ques…
Hierarchical Graph Topic Modeling with Topic Tree-based Transformer
Delvin Ce Zhang, Menglin Yang, Xiaobao Wu +2
Textual documents are commonly connected in a hierarchical graph structure where a central document links to others with an exponentially growing connectivity. Though Hyperbolic Gr…
Low-Rank Adaptation for Foundation Models: A Comprehensive Review
Menglin Yang, Jialin Chen, Jinkai Tao +9
The rapid advancement of foundation modelslarge-scale neural networks trained on diverse, extensive datasetshas revolutionized artificial intelligence, enabling unprecedented advan…
Towards Pattern-aware Data Augmentation for Temporal Knowledge Graph Completion
Jiasheng Zhang, Deqiang Ouyang, Shuang Liang +1
Predicting missing facts for temporal knowledge graphs (TKGs) is a fundamental task, called temporal knowledge graph completion (TKGC). One key challenge in this task is the imbala…
GraphTool-Instruction: Revolutionizing Graph Reasoning in LLMs through Decomposed Subtask Instruction
Rongzheng Wang, Shuang Liang, Qizhi Chen +2
Large language models (LLMs) have been demonstrated to possess the capabilities to understand fundamental graph properties and address various graph reasoning tasks. Existing metho…
Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation
Mohamed A. Radwan, Himaghna Bhattacharjee, Quinn Lanners +4
We propose a domain-adapted reward model that works alongside an Offline A/B testing system for evaluating ranking models. This approach effectively measures reward for ranking mod…
Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability
Jiasheng Zhang, Rex Ying, Jie Shao
Temporal knowledge graphs (TKGs) are valuable resources for capturing evolving relationships among entities, yet they are often plagued by noise, necessitating robust anomaly detec…
LitFM: A Retrieval Augmented Structure-aware Foundation Model For Citation Graphs
Jiasheng Zhang, Jialin Chen, Ali Maatouk +6
With the advent of large language models (LLMs), managing scientific literature via LLMs has become a promising direction of research. However, existing approaches often overlook t…
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs
Jiasheng Zhang, Jialin Chen, Menglin Yang +4
Dynamic text-attributed graphs (DyTAGs) are prevalent in various real-world scenarios, where each node and edge are associated with text descriptions, and both the graph structure…