119 citations · 185 across the 16 of their papers we have counts for
25 papers
Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles
Shuquan Ye, Yujia Xie, Dongdong Chen +4
This paper focuses on analyzing and improving the commonsense ability of recent popular vision-language (VL) models. Despite the great success, we observe that existing VL-models s…
Empowering Language Models with Knowledge Graph Reasoning for Question Answering
Ziniu Hu, Yichong Xu, Wenhao Yu +5
Answering open-domain questions requires world knowledge about in-context entities. As pre-trained Language Models (LMs) lack the power to store all required knowledge, external kn…
Retrieval Augmentation for Commonsense Reasoning: A Unified Approach
Wenhao Yu, Chenguang Zhu, Zhihan Zhang +4
A common thread of retrieval-augmented methods in the existing literature focuses on retrieving encyclopedic knowledge, such as Wikipedia, which facilitates well-defined entity and…
Towards a Unified Multi-Dimensional Evaluator for Text Generation
Ming Zhong, Yang Liu, Da Yin +6
Multi-dimensional evaluation is the dominant paradigm for human evaluation in Natural Language Generation (NLG), i.e., evaluating the generated text from multiple explainable dimen…
Task Compass: Scaling Multi-task Pre-training with Task Prefix
Zhuosheng Zhang, Shuohang Wang, Yichong Xu +6
Leveraging task-aware annotated data as supervised signals to assist with self-supervised learning on large-scale unlabeled data has become a new trend in pre-training language mod…
FAST: Improving Controllability for Text Generation with Feedback Aware Self-Training
Junyi Chai, Reid Pryzant, Victor Ye Dong +3
Controllable text generation systems often leverage control codes to direct various properties of the output like style and length. Inspired by recent work on causal inference for…