35 citations · 81 across the 8 of their papers we have counts for
8 papers
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…
SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
Liang Wang, Wei Zhao, Zhuoyu Wei +1
Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from…
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems
Wei Zhao, Mingyue Shang, Yang Liu +2
Automatic math word problem solving has attracted growing attention in recent years. The evaluation datasets used by previous works have serious limitations in terms of scale and d…
Investigating Label Bias in Beam Search for Open-ended Text Generation
Liang Wang, Jinlong Liu, Jingming Liu
Beam search is an effective and widely used decoding algorithm in many sequence-to-sequence (seq2seq) text generation tasks. However, in open-ended text generation, beam search is…
Denoising based Sequence-to-Sequence Pre-training for Text Generation
Liang Wang, Wei Zhao, Ruoyu Jia +2
This paper presents a new sequence-to-sequence (seq2seq) pre-training method PoDA (Pre-training of Denoising Autoencoders), which learns representations suitable for text generatio…
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data
Wei Zhao, Liang Wang, Kewei Shen +2
Neural machine translation systems have become state-of-the-art approaches for Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented architecture for…
Multi-Perspective Context Aggregation for Semi-supervised Cloze-style Reading Comprehension
Liang Wang, Sujian Li, Wei Zhao +4
Cloze-style reading comprehension has been a popular task for measuring the progress of natural language understanding in recent years. In this paper, we design a novel multi-persp…
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension
Liang Wang, Meng Sun, Wei Zhao +2
This paper describes our system for SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. We use Three-way Attentive Networks (TriAN) to model interactions betwe…