35 citations · 128 across the 9 of their papers we have counts for
24 papers
Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models
Xichen Pan, Pengda Qin, Yuhong Li +2
Conditioned diffusion models have demonstrated state-of-the-art text-to-image synthesis capacity. Recently, most works focus on synthesizing independent images; While for real-worl…
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text
Wenhu Chen, Hexiang Hu, Xi Chen +2
While language Models store a massive amount of world knowledge implicitly in their parameters, even very large models often fail to encode information about rare entities and even…
Explanations from Large Language Models Make Small Reasoners Better
Shiyang Li, Jianshu Chen, Yelong Shen +9
Integrating free-text explanations to in-context learning of large language models (LLM) is shown to elicit strong reasoning capabilities along with reasonable explanations. In thi…
Modeling Token-level Uncertainty to Learn Unknown Concepts in SLU via Calibrated Dirichlet Prior RNN
Yilin Shen, Wenhu Chen, Hongxia Jin
One major task of spoken language understanding (SLU) in modern personal assistants is to extract semantic concepts from an utterance, called slot filling. Although existing slot f…
KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation
Wenhu Chen, Yu Su, Xifeng Yan +1
Data-to-text generation has recently attracted substantial interests due to its wide applications. Existing methods have shown impressive performance on an array of tasks. However,…
Unsupervised Multi-hop Question Answering by Question Generation
Liangming Pan, Wenhu Chen, Wenhan Xiong +2
Obtaining training data for multi-hop question answering (QA) is time-consuming and resource-intensive. We explore the possibility to train a well-performed multi-hop QA model with…