159 citations · 218 across the 12 of their papers we have counts for
5 papers · 1 filter
Towards More Efficient Insertion Transformer with Fractional Positional Encoding
Zhisong Zhang, Yizhe Zhang, Bill Dolan
Auto-regressive neural sequence models have been shown to be effective across text generation tasks. However, their left-to-right decoding order prevents generation from being para…
Automatic Document Sketching: Generating Drafts from Analogous Texts
Zeqiu Wu, Michel Galley, Chris Brockett +2
The advent of large pre-trained language models has made it possible to make high-quality predictions on how to add or change a sentence in a document. However, the high branching…
An Adversarially-Learned Turing Test for Dialog Generation Models
Xiang Gao, Yizhe Zhang, Michel Galley +1
The design of better automated dialogue evaluation metrics offers the potential of accelerate evaluation research on conversational AI. However, existing trainable dialogue evaluat…
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation
Tianyu Liu, Yizhe Zhang, Chris Brockett +4
Large pretrained generative models like GPT-3 often suffer from hallucinating non-existent or incorrect content, which undermines their potential merits in real applications. Exist…
What Makes Good In-Context Examples for GPT-?
Jiachang Liu, Dinghan Shen, Yizhe Zhang +3
GPT- has attracted lots of attention due to its superior performance across a wide range of NLP tasks, especially with its powerful and versatile in-context few-shot learning ab…