16 citations · 56 across the 26 of their papers we have counts for
10 papers · 1 filter
M^2ConceptBase: A Fine-Grained Aligned Concept-Centric Multimodal Knowledge Base
Zhiwei Zha, Jiaan Wang, Zhixu Li +3
Multimodal knowledge bases (MMKBs) provide cross-modal aligned knowledge crucial for multimodal tasks. However, the images in existing MMKBs are generally collected for entities in…
AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities
Jingdan Zhang, Jiaan Wang, Xiaodan Wang +2
Multi-modal knowledge graphs (MMKGs) combine different modal data (e.g., text and image) for a comprehensive understanding of entities. Despite the recent progress of large-scale M…
Cross-Lingual Knowledge Editing in Large Language Models
Jiaan Wang, Yunlong Liang, Zengkui Sun +3
Knowledge editing aims to change language models' performance on several special cases (i.e., editing scope) by infusing the corresponding expected knowledge into them. With the re…
Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model
Jiaan Wang, Jianfeng Qu, Yunlong Liang +4
Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence. Nevertheless, existing CKGs are…
Unified Model Learning for Various Neural Machine Translation
Yunlong Liang, Fandong Meng, Jinan Xu +3
Existing neural machine translation (NMT) studies mainly focus on developing dataset-specific models based on data from different tasks (e.g., document translation and chat transla…
Towards Unifying Multi-Lingual and Cross-Lingual Summarization
Jiaan Wang, Fandong Meng, Duo Zheng +4
To adapt text summarization to the multilingual world, previous work proposes multi-lingual summarization (MLS) and cross-lingual summarization (CLS). However, these two tasks have…
DTV: Dual Knowledge Distillation and Target-oriented Vision Modeling for Many-to-Many Multimodal Summarization
Yunlong Liang, Fandong Meng, Jiaan Wang +3
Many-to-many multimodal summarization (MS) task aims to generate summaries in any language with document inputs in any language and the corresponding image sequence, which esse…
When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
Yuxuan Cao, Jiarong Xu, Carl Yang +5
In recent years, graph pre-training has gained significant attention, focusing on acquiring transferable knowledge from unlabeled graph data to improve downstream performance. Desp…
Is ChatGPT a Good NLG Evaluator? A Preliminary Study
Jiaan Wang, Yunlong Liang, Fandong Meng +6
Recently, the emergence of ChatGPT has attracted wide attention from the computational linguistics community. Many prior studies have shown that ChatGPT achieves remarkable perform…
Zero-Shot Cross-Lingual Summarization via Large Language Models
Jiaan Wang, Yunlong Liang, Fandong Meng +4
Given a document in a source language, cross-lingual summarization (CLS) aims to generate a summary in a different target language. Recently, the emergence of Large Language Models…