activity
20182022
most citedCoaCor: Code Annotation for Code Retrieval with Reinforcement Learning

97 citations · 109 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG202112 cited

Learning Structural Edits via Incremental Tree Transformations

Ziyu Yao, Frank F. Xu, Pengcheng Yin +2

While most neural generative models generate outputs in a single pass, the human creative process is usually one of iterative building and refinement. Recent work has proposed mode…

cs.CL2020

An Imitation Game for Learning Semantic Parsers from User Interaction

Ziyu Yao, Yiqi Tang, Wen-tau Yih +2

Despite the widely successful applications, bootstrapping and fine-tuning semantic parsers are still a tedious process with challenges such as costly data annotation and privacy ri…

cs.CL2019

Model-based Interactive Semantic Parsing: A Unified Framework and A Text-to-SQL Case Study

Ziyu Yao, Yu Su, Huan Sun +1

As a promising paradigm, interactive semantic parsing has shown to improve both semantic parsing accuracy and user confidence in the results. In this paper, we propose a new, unifi…

cs.CL2019

Reinforced Dynamic Reasoning for Conversational Question Generation

Boyuan Pan, Hao Li, Ziyu Yao +2

This paper investigates a new task named Conversational Question Generation (CQG) which is to generate a question based on a passage and a conversation history (i.e., previous turn…

cs.SE201997 cited

CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning

Ziyu Yao, Jayavardhan Reddy Peddamail, Huan Sun

To accelerate software development, much research has been performed to help people understand and reuse the huge amount of available code resources. Two important tasks have been…

cs.CL2018

Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning

Ziyu Yao, Xiujun Li, Jianfeng Gao +2

Given a text description, most existing semantic parsers synthesize a program in one shot. However, it is quite challenging to produce a correct program solely based on the descrip…