10 papers
GRAND-HC: Graph-Refined Author Name Disambiguation
Yuanhao Sun, Zhouyang Jin, Yi Xu +5
From-Scratch Name Disambiguation (SND) groups papers sharing an ambiguous name into clusters of distinct real-world authors. Existing methods suffer from two critical limitations:…
LEAP: Unlocking dLLM Parallelism via Lookahead Early-Convergence Token Detection
Haohui Zhang, Zhiye Wang, Xiaoying Gan +2
Diffusion Language Models (dLLMs) have garnered significant attention for their potential in highly parallel processing. The parallel capabilities of existing dLLMs stem from the a…
Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities
Ze Zhao, Yuhui He, Lyuwen Wu +6
Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at capturing relational dynamics,…
<SOG_k>: One LLM Token for Explicit Graph Structural Understanding
Jingyao Wu, Bin Lu, Zijun Di +5
Large language models show great potential in unstructured data understanding, but still face significant challenges with graphs due to their structural hallucination. Existing app…
Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression
Zijun Di, Bin Lu, Huquan Kang +5
Large language models (LLMs) have demonstrated promising capabilities in Text-Attributed Graph (TAG) understanding. Recent studies typically focus on verbalizing the graph structur…
CHAINSFORMER: Numerical Reasoning on Knowledge Graphs from a Chain Perspective
Ze Zhao, Bin Lu, Xiaoying Gan +3
Reasoning over Knowledge Graphs (KGs) plays a pivotal role in knowledge graph completion or question answering systems, providing richer and more accurate triples and attributes. A…
AceParse: A Comprehensive Dataset with Diverse Structured Texts for Academic Literature Parsing
Huawei Ji, Cheng Deng, Bo Xue +6
With the development of data-centric AI, the focus has shifted from model-driven approaches to improving data quality. Academic literature, as one of the crucial types, is predomin…
AutoFAIR : Automatic Data FAIRification via Machine Reading
Tingyan Ma, Wei Liu, Bin Lu +4
The explosive growth of data fuels data-driven research, facilitating progress across diverse domains. The FAIR principles emerge as a guiding standard, aiming to enhance the finda…
OXYGENERATOR: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
Bin Lu, Ze Zhao, Luyu Han +7
Accurately reconstructing the global ocean deoxygenation over a century is crucial for assessing and protecting marine ecosystem. Existing expert-dominated numerical simulations fa…
Temporal Generalization Estimation in Evolving Graphs
Bin Lu, Tingyan Ma, Xiaoying Gan +4
Graph Neural Networks (GNNs) are widely deployed in vast fields, but they often struggle to maintain accurate representations as graphs evolve. We theoretically establish a lower b…