b'Xinyun Chen'

research

∙ 09/07/2023

Large Language Models as Optimizers

Optimization is ubiquitous. While derivative-based algorithms have been ...

0 Chengrun Yang, et al. ∙

research

∙ 08/31/2023

BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge

Pre-trained language models like ChatGPT have significantly improved cod...

1 Xiangru Tang, et al. ∙

research

∙ 05/26/2023

Large Language Models as Tool Makers

Recent research shows the potential of enhancing the problem-solving abi...

7 Tianle Cai, et al. ∙

research

∙ 05/24/2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts

The explosive growth of language models and their applications have led ...

0 Sheng Shen, et al. ∙

research

∙ 05/15/2023

Symbol tuning improves in-context learning in language models

We present symbol tuning - finetuning language models on in-context inpu...

0 Jerry Wei, et al. ∙

research

∙ 04/11/2023

Teaching Large Language Models to Self-Debug

Large language models (LLMs) have achieved impressive performance on cod...

0 Xinyun Chen, et al. ∙

research

∙ 04/01/2023

DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection

We propose and release a new vulnerable source code dataset. We curate t...

0 Yizheng Chen, et al. ∙

research

∙ 03/07/2023

Larger language models do in-context learning differently

We study how in-context learning (ICL) in language models is affected by...

0 Jerry Wei, et al. ∙

research

∙ 03/06/2023

Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution

We investigate an optimization problem in a queueing system where the se...

0 Xinyun Chen, et al. ∙

research

∙ 01/31/2023

Large Language Models Can Be Easily Distracted by Irrelevant Context

Large language models have achieved impressive performance on various na...

7 Freda Shi, et al. ∙

research

∙ 11/16/2022

Data-pooling Reinforcement Learning for Personalized Healthcare Intervention

Motivated by the emerging needs of personalized preventative interventio...

0 Xinyun Chen, et al. ∙

research

∙ 10/26/2022

Benchmarking Language Models for Code Syntax Understanding

Pre-trained language models have demonstrated impressive performance in ...

0 Da Shen, et al. ∙

research

∙ 09/29/2022

Compositional Semantic Parsing with Large Language Models

Humans can reason compositionally when presented with new tasks. Previou...

0 Andrew Drozdov, et al. ∙

research

∙ 05/04/2022

Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignment

In text-to-SQL tasks – as in much of NLP – compositional generalization ...

0 Yujian Gan, et al. ∙

research

∙ 02/08/2022

Competition-Level Code Generation with AlphaCode

Programming is a powerful and ubiquitous problem-solving tool. Developin...

0 Yujia Li, et al. ∙

research

∙ 12/16/2021

Learning Bounded Context-Free-Grammar via LSTM and the Transformer:Difference and Explanations

Long Short-Term Memory (LSTM) and Transformers are two popular neural ar...

15 Hui Shi, et al. ∙

research

∙ 10/28/2021

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

Knowledge graphs (KGs) capture knowledge in the form of head–relation–ta...

6 Hongyu Ren, et al. ∙

research

∙ 09/11/2021

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

Deep neural networks (DNNs) are vulnerable to adversarial noises, which ...

4 Shiyu Tang, et al. ∙

research

∙ 09/11/2021

Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization

Recently, there has been significant progress in studying neural network...

0 Yujian Gan, et al. ∙

research

∙ 09/11/2021

Natural SQL: Making SQL Easier to Infer from Natural Language Specifications

Addressing the mismatch between natural language descriptions and the co...

0 Yujian Gan, et al. ∙

research

∙ 07/08/2021

A Note on General Statistics of Publicly Accessible Knowledge Bases

Knowledge bases are prevalent in various domains and have been widely us...

0 Feixiang Wang, et al. ∙

research

∙ 06/29/2021

Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages

Program synthesis from input-output examples has been a long-standing ch...

3 Xinyun Chen, et al. ∙

research

∙ 06/26/2021

SpreadsheetCoder: Formula Prediction from Semi-structured Context

Spreadsheet formula prediction has been an important program synthesis p...

1 Xinyun Chen, et al. ∙

research

∙ 06/24/2021

Understanding the Spread of COVID-19 Epidemic: A Spatio-Temporal Point Process View

Since the first coronavirus case was identified in the U.S. on Jan. 21, ...

19 Shuang Li, et al. ∙

research

∙ 06/02/2021

Towards Robustness of Text-to-SQL Models against Synonym Substitution

Recently, there has been significant progress in studying neural network...

0 Yujian Gan, et al. ∙

research

∙ 04/12/2021

A High-fidelity, Machine-learning Enhanced Queueing Network Simulation Model for Hospital Ultrasound Operations

We collaborate with a large teaching hospital in Shenzhen, China and bui...

0 Yihan Pan, et al. ∙

research

∙ 02/25/2021

Understanding Robustness in Teacher-Student Setting: A New Perspective

Adversarial examples have appeared as a ubiquitous property of machine l...

13 Zhuolin Yang, et al. ∙

research

∙ 12/18/2020

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

As machine learning systems grow in scale, so do their training data req...

71 Micah Goldblum, et al. ∙

research

∙ 12/03/2020

Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization

There is now extensive evidence demonstrating that deep neural networks ...

0 Aishan Liu, et al. ∙

research

∙ 09/07/2020

An online learning approach to dynamic pricing and capacity sizing in service systems

We study a dynamic pricing and capacity sizing problem in a GI/GI/1 queu...

0 Xinyun Chen, et al. ∙

research

∙ 08/15/2020

Compositional Generalization via Neural-Symbolic Stack Machines

Despite achieving tremendous success, existing deep learning models have...

6 Xinyun Chen, et al. ∙

research

∙ 07/16/2020

Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis

The use of deep learning techniques has achieved significant progress fo...

9 Kavi Gupta, et al. ∙

research

∙ 07/12/2020

Perfect Sampling of Multivariate Hawkes Process

As an extension of self-exciting Hawkes process, the multivariate Hawkes...

0 Xinyun Chen, et al. ∙

research

∙ 05/19/2020

Adversarial Attacks for Embodied Agents

Adversarial attacks are valuable for providing insights into the blind-s...

40 Aishan Liu, et al. ∙

research

∙ 11/17/2019

REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data

Deep neural networks (DNNs) have achieved tremendous success in various ...

0 Xinyun Chen, et al. ∙

research

∙ 10/10/2019

Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies

We consider off-policy policy evaluation when the trajectory data are ge...

13 Xinyun Chen, et al. ∙

research

∙ 06/28/2019

A Neural-based Program Decompiler

Reverse engineering of binary executables is a critical problem in the c...

0 Cheng Fu, et al. ∙

research

∙ 09/30/2018

Learning to Progressively Plan

For problem solving, making reactive decisions based on problem descript...

0 Xinyun Chen, et al. ∙

research

∙ 02/11/2018

Tree-to-tree Neural Networks for Program Translation

Program translation is an important tool to migrate legacy code in one l...

0 Xinyun Chen, et al. ∙

research

∙ 12/15/2017

Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Deep learning models have achieved high performance on many tasks, and t...

0 Xinyun Chen, et al. ∙

research

∙ 09/25/2017

Can you fool AI with adversarial examples on a visual Turing test?

Deep learning has achieved impressive results in many areas of Computer ...

0 Xiaojun Xu, et al. ∙

research

∙ 06/05/2017

Learning Neural Programs To Parse Programs

In this work, we study an important problem: learning programs from inpu...

0 Xinyun Chen, et al. ∙

research

∙ 11/07/2016

Latent Attention For If-Then Program Synthesis

Automatic translation from natural language descriptions into programs i...

0 Xinyun Chen, et al. ∙

research

∙ 04/09/2016

A General Retraining Framework for Scalable Adversarial Classification

Traditional classification algorithms assume that training and test data...

0 Bo Li, et al. ∙

Xinyun Chen

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