6 citations · 21 across the 14 of their papers we have counts for
14 papers
Character-Centric Story Visualization via Visual Planning and Token Alignment
Hong Chen, Rujun Han, Te-Lin Wu +2
Story visualization advances the traditional text-to-image generation by enabling multiple image generation based on a complete story. This task requires machines to 1) understand…
StoryER: Automatic Story Evaluation via Ranking, Rating and Reasoning
Hong Chen, Duc Minh Vo, Hiroya Takamura +2
Existing automatic story evaluation methods place a premium on story lexical level coherence, deviating from human preference. We go beyond this limitation by considering a novel \…
AntCritic: Argument Mining for Free-Form and Visually-Rich Financial Comments
Huadai Liu, Wenqiang Xu, Xuan Lin +3
Argument mining aims to detect all possible argumentative components and identify their relationships automatically. As a thriving task in natural language processing, there has be…
Go Back in Time: Generating Flashbacks in Stories with Event Temporal Prompts
Rujun Han, Hong Chen, Yufei Tian +1
Stories or narratives are comprised of a sequence of events. To compose interesting stories, professional writers often leverage a creative writing technique called flashback that…
NOC-REK: Novel Object Captioning with Retrieved Vocabulary from External Knowledge
Duc Minh Vo, Hong Chen, Akihiro Sugimoto +1
Novel object captioning aims at describing objects absent from training data, with the key ingredient being the provision of object vocabulary to the model. Although existing metho…
Injecting Numerical Reasoning Skills into Knowledge Base Question Answering Models
Yu Feng, Jing Zhang, Xiaokang Zhang +3
Embedding-based methods are popular for Knowledge Base Question Answering (KBQA), but few current models have numerical reasoning skills and thus struggle to answer ordinal constra…
A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation
Bowen Hao, Hongzhi Yin, Jing Zhang +2
Cold-start problem is a fundamental challenge for recommendation tasks. The recent self-supervised learning (SSL) on Graph Neural Networks (GNNs) model, PT-GNN, pre-trains the GNN…
SciXGen: A Scientific Paper Dataset for Context-Aware Text Generation
Hong Chen, Hiroya Takamura, Hideki Nakayama
Generating texts in scientific papers requires not only capturing the content contained within the given input but also frequently acquiring the external information called \textit…
GraphPlan: Story Generation by Planning with Event Graph
Hong Chen, Raphael Shu, Hiroya Takamura +1
Story generation is a task that aims to automatically produce multiple sentences to make up a meaningful story. This task is challenging because it requires high-level understandin…
Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling
Hong Chen, Yifei Huang, Hiroya Takamura +1
Visual storytelling is a task of generating relevant and interesting stories for given image sequences. In this work we aim at increasing the diversity of the generated stories whi…
CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking
Bo Chen, Jing Zhang, Xiaokang Zhang +6
Expert finding, a popular service provided by many online websites such as Expertise Finder, LinkedIn, and AMiner, is beneficial to seeking candidate qualifications, consultants, a…
CONNA: Addressing Name Disambiguation on The Fly
Bo Chen, Jing Zhang, Jie Tang +5
Name disambiguation is a key and also a very tough problem in many online systems such as social search and academic search. Despite considerable research, a critical issue that ha…
PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution
Hong Chen, Zhenhua Fan, Hao Lu +2
We introduce PreCo, a large-scale English dataset for coreference resolution. The dataset is designed to embody the core challenges in coreference, such as entity representation, b…
Semantic Aware Attention Based Deep Object Co-segmentation
Hong Chen, Yifei Huang, Hideki Nakayama
Object co-segmentation is the task of segmenting the same objects from multiple images. In this paper, we propose the Attention Based Object Co-Segmentation for object co-segmentat…