159 citations · 183 across the 6 of their papers we have counts for
10 papers
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…
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…
Narrative Incoherence Detection
Deng Cai, Yizhe Zhang, Yichen Huang +2
We propose the task of narrative incoherence detection as a new arena for inter-sentential semantic understanding: Given a multi-sentence narrative, decide whether there exist any…
Text Editing by Command
Felix Faltings, Michel Galley, Gerold Hintz +4
A prevailing paradigm in neural text generation is one-shot generation, where text is produced in a single step. The one-shot setting is inadequate, however, when the constraints t…
Substance over Style: Document-Level Targeted Content Transfer
Allison Hegel, Sudha Rao, Asli Celikyilmaz +1
Existing language models excel at writing from scratch, but many real-world scenarios require rewriting an existing document to fit a set of constraints. Although sentence-level re…
Dialogue Response Ranking Training with Large-Scale Human Feedback Data
Xiang Gao, Yizhe Zhang, Michel Galley +2
Existing open-domain dialog models are generally trained to minimize the perplexity of target human responses. However, some human replies are more engaging than others, spawning m…