156 citations · 168 across the 7 of their papers we have counts for
7 papers
PTVD: A Large-Scale Plot-Oriented Multimodal Dataset Based on Television Dramas
Chen Li, Xutan Peng, Teng Wang +5
Art forms such as movies and television (TV) dramas are reflections of the real world, which have attracted much attention from the multimodal learning community recently. However,…
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
Ce Zhou, Qian Li, Chen Li +16
Pretrained Foundation Models (PFMs) are regarded as the foundation for various downstream tasks with different data modalities. A PFM (e.g., BERT, ChatGPT, and GPT-4) is trained on…
Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
Jinghui Si, Xutan Peng, Chen Li +2
Event Extraction bridges the gap between text and event signals. Based on the assumption of trigger-argument dependency, existing approaches have achieved state-of-the-art performa…
Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral College
Chen Li, Xutan Peng, Hao Peng +4
Recently, graph-based algorithms have drawn much attention because of their impressive success in semi-supervised setups. For better model performance, previous studies learn to tr…
Understanding Linearity of Cross-Lingual Word Embedding Mappings
Xutan Peng, Mark Stevenson, Chenghua Lin +1
The technique of Cross-Lingual Word Embedding (CLWE) plays a fundamental role in tackling Natural Language Processing challenges for low-resource languages. Its dominant approaches…
Modeling relation paths for knowledge base completion via joint adversarial training
Chen Li, Xutan Peng, Shanghang Zhang +5
Knowledge Base Completion (KBC), which aims at determining the missing relations between entity pairs, has received increasing attention in recent years. Most existing KBC methods…
A Lightweight Music Texture Transfer System
Xutan Peng, Chen Li, Zhi Cai +3
Deep learning researches on the transformation problems for image and text have raised great attention. However, present methods for music feature transfer using neural networks ar…