Search Results for author: Qizhe Xie

Found 18 papers, 10 papers with code

InstructCoder: Instruction Tuning Large Language Models for Code Editing

1 code implementation31 Oct 2023 Kaixin Li, Qisheng Hu, Xu Zhao, Hui Chen, Yuxi Xie, Tiedong Liu, Qizhe Xie, Junxian He

In this work, we explore the use of Large Language Models (LLMs) to edit code based on user instructions.

SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

2 code implementations3 Aug 2023 Keyu Duan, Qian Liu, Tat-Seng Chua, Shuicheng Yan, Wei Tsang Ooi, Qizhe Xie, Junxian He

More recently, with the rapid development of language models (LMs), researchers have focused on leveraging LMs to facilitate the learning of TGs, either by jointly training them in a computationally intensive framework (merging the two stages), or designing complex self-supervised training tasks for feature extraction (enhancing the first stage).

Feature Engineering Graph Learning +3

Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering

1 code implementation11 Jun 2023 Hai Ye, Qizhe Xie, Hwee Tou Ng

In this work, we study multi-source test-time model adaptation from user feedback, where K distinct models are established for adaptation.

Decision Making Extractive Question-Answering +2

CodeInstruct: Empowering Language Models to Edit Code

1 code implementation Github 2023 Qisheng Hu*, Kaixin Li*, Xu Zhao, Yuxi Xie, Tiedong Liu, Hui Chen, Qizhe Xie, Junxian He

In this work, we explore the use of large language models (LLMs) to edit code based on user instructions, covering a broad range of implicit tasks such as comment insertion, code optimization, and code refactoring.

Self-Evaluation Guided Beam Search for Reasoning

no code implementations NeurIPS 2023 Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, Xu Zhao, Min-Yen Kan, Junxian He, Qizhe Xie

Stochastic beam search balances exploitation and exploration of the search space with temperature-controlled randomness.

Arithmetic Reasoning GSM8K +3

Meta Pseudo Labels

9 code implementations CVPR 2021 Hieu Pham, Zihang Dai, Qizhe Xie, Minh-Thang Luong, Quoc V. Le

We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90. 2% on ImageNet, which is 1. 6% better than the existing state-of-the-art.

Meta-Learning Semi-Supervised Image Classification

Self-training with Noisy Student improves ImageNet classification

13 code implementations CVPR 2020 Qizhe Xie, Minh-Thang Luong, Eduard Hovy, Quoc V. Le

During the learning of the student, we inject noise such as dropout, stochastic depth, and data augmentation via RandAugment to the student so that the student generalizes better than the teacher.

Ranked #16 on Image Classification on ImageNet ReaL (using extra training data)

Data Augmentation General Classification +1

Unsupervised Data Augmentation for Consistency Training

20 code implementations NeurIPS 2020 Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, Quoc V. Le

In this work, we present a new perspective on how to effectively noise unlabeled examples and argue that the quality of noising, specifically those produced by advanced data augmentation methods, plays a crucial role in semi-supervised learning.

Image Augmentation Semi-Supervised Image Classification +2

The Profiling Machine: Active Generalization over Knowledge

no code implementations1 Oct 2018 Filip Ilievski, Eduard Hovy, Qizhe Xie, Piek Vossen

The human mind is a powerful multifunctional knowledge storage and management system that performs generalization, type inference, anomaly detection, stereotyping, and other tasks.

Anomaly Detection Management

From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction

1 code implementation ACL 2018 Zihang Dai, Qizhe Xie, Eduard Hovy

In this work, we study the credit assignment problem in reward augmented maximum likelihood (RAML) learning, and establish a theoretical equivalence between the token-level counterpart of RAML and the entropy regularized reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

Large-scale Cloze Test Dataset Designed by Teachers

no code implementations ICLR 2018 Qizhe Xie, Guokun Lai, Zihang Dai, Eduard Hovy

Cloze test is widely adopted in language exams to evaluate students' language proficiency.

Cloze Test

Controllable Invariance through Adversarial Feature Learning

no code implementations NeurIPS 2017 Qizhe Xie, Zihang Dai, Yulun Du, Eduard Hovy, Graham Neubig

Learning meaningful representations that maintain the content necessary for a particular task while filtering away detrimental variations is a problem of great interest in machine learning.

General Classification Image Classification +1

An Interpretable Knowledge Transfer Model for Knowledge Base Completion

no code implementations ACL 2017 Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard Hovy

Knowledge bases are important resources for a variety of natural language processing tasks but suffer from incompleteness.

Knowledge Base Completion Transfer Learning

Recurrent Polynomial Network for Dialogue State Tracking

no code implementations14 Jul 2015 Kai Sun, Qizhe Xie, Kai Yu

Dialogue state tracking (DST) is a process to estimate the distribution of the dialogue states as a dialogue progresses.

dialog state tracking Dialogue State Tracking

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