一作ACL 2026Poster· Natural Language Processing
CITE : Benchmarking Heterogeneous Text-Attributed Graph Models
Chenghao Zhang · Qingqing Long · Ludi Wang · Wenjuan Cui · Jianjun Yu · Yi Du
摘要
Recent advances in large language models (LLMs) and text-aware graph learning have increased interest in reasoning over text-attributed graphs(TAGs). In many real-world settings, such graphs are inherently heterogeneous, with most existing benchmarks remaining largely homogeneous in structure. As...