Frank F. Xu | DeepAI

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Yu Zhang
406 publications
Graham Neubig
243 publications
Dan Roth
151 publications
Jiawei Han
140 publications
Nan Duan
128 publications
Xiang Ren
120 publications
Qi Li
109 publications
Yiming Yang
76 publications
Qi Zhu
75 publications
Jian Peng
67 publications
Xuan Wang
62 publications

∙ 05/11/2023

Active Retrieval Augmented Generation

Despite the remarkable ability of large language models (LMs) to compreh...

0 Zhengbao Jiang, et al. ∙

∙ 01/07/2023

Why do Nearest Neighbor Language Models Work?

Language models (LMs) compute the probability of a text by sequentially ...

0 Frank F. Xu, et al. ∙

∙ 07/13/2022

DocCoder: Generating Code by Retrieving and Reading Docs

Natural-language-to-code models learn to generate a code snippet given a...

0 Shuyan Zhou, et al. ∙

∙ 03/16/2022

MCoNaLa: A Benchmark for Code Generation from Multiple Natural Languages

While there has been a recent burgeoning of applications at the intersec...

0 Zhiruo Wang, et al. ∙

∙ 02/26/2022

A Systematic Evaluation of Large Language Models of Code

Large language models (LMs) of code have recently shown tremendous promi...

0 Frank F. Xu, et al. ∙

∙ 01/28/2022

Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval

Retrieval-based language models (R-LM) model the probability of natural ...

0 Uri Alon, et al. ∙

∙ 10/06/2021

Capturing Structural Locality in Non-parametric Language Models

Structural locality is a ubiquitous feature of real-world datasets, wher...

0 Frank F. Xu, et al. ∙

∙ 01/28/2021

Learning Structural Edits via Incremental Tree Transformations

While most neural generative models generate outputs in a single pass, t...

10 Ziyu Yao, et al. ∙

∙ 01/27/2021

In-IDE Code Generation from Natural Language: Promise and Challenges

A great part of software development involves conceptualizing or communi...

0 Frank F. Xu, et al. ∙

∙ 05/02/2020

A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos

Procedural knowledge, which we define as concrete information about the ...

6 Frank F. Xu, et al. ∙

∙ 05/01/2020

Minimally Supervised Categorization of Text with Metadata

Document categorization, which aims to assign a topic label to each docu...

0 Yu Zhang, et al. ∙

∙ 04/20/2020

Incorporating External Knowledge through Pre-training for Natural Language to Code Generation

Open-domain code generation aims to generate code in a general-purpose p...

0 Frank F. Xu, et al. ∙

∙ 11/28/2019

How Can We Know What Language Models Know?

Recent work has presented intriguing results examining the knowledge con...

0 Zhengbao Jiang, et al. ∙

∙ 10/16/2019

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories

GitHub has become an important platform for code sharing and scientific ...

11 Yu Zhang, et al. ∙

∙ 08/20/2019

StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible

Blind people frequently encounter inaccessible dynamic touchscreens in t...

0 Anhong Guo, et al. ∙

∙ 10/14/2018

Incorporating Diversity into Influential Node Mining

Diversity is a crucial criterion in many ranking and mining tasks. In th...

0 Yu Zhang, et al. ∙

∙ 04/26/2018

Open Information Extraction with Global Structure Constraints

Extracting entities and their relations from text is an important task f...

0 Qi Zhu, et al. ∙

∙ 04/26/2018

Integrating Local Context and Global Cohesiveness for Open Information Extraction

Extracting entities and their relations from text is an important task f...

0 Qi Zhu, et al. ∙

∙ 11/11/2017

Commonsense LocatedNear Relation Extraction

LocatedNear relation describes two typically co-located objects, which i...

0 Frank F. Xu, et al. ∙

∙ 10/30/2017

Indirect Supervision for Relation Extraction using Question-Answer Pairs

Automatic relation extraction (RE) for types of interest is of great imp...

0 Zeqiu Wu, et al. ∙

∙ 09/13/2017

Empower Sequence Labeling with Task-Aware Neural Language Model

Linguistic sequence labeling is a general modeling approach that encompa...

0 Liyuan Liu, et al. ∙

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