4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 2 cited
MMDocBench: Benchmarking Large Vision-Language Models for Fine-Grained Visual Document Understanding
Fengbin Zhu, Ziyang Liu, Xiang Yao Ng +6
Large Vision-Language Models (LVLMs) have achieved remarkable performance in many vision-language tasks, yet their capabilities in fine-grained visual understanding remain insuffic…
cs.CL2024★ 4 cited
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
Fengbin Zhu, Ziyang Liu, Fuli Feng +3
In this work, we address question answering (QA) over a hybrid of tabular and textual data that are very common content on the Web (e.g. SEC filings), where discrete reasoning capa…
cs.SI2022
TeKo: Text-Rich Graph Neural Networks with External Knowledge
Zhizhi Yu, Di Jin, Jianguo Wei +5
Graph Neural Networks (GNNs) have gained great popularity in tackling various analytical tasks on graph-structured data (i.e., networks). Typical GNNs and their variants follow a m…