Search Results for author: WeiJie Chen

Found 15 papers, 8 papers with code

Unraveling the Mystery of Artifacts in Machine Generated Text

1 code implementation LREC 2022 Jiashu Pu, Ziyi Huang, Yadong Xi, Guandan Chen, WeiJie Chen, Rongsheng Zhang

As neural Text Generation Models (TGM) have become more and more capable of generating text indistinguishable from human-written ones, the misuse of text generation technologies can have serious ramifications.

Text Generation

Label Matching Semi-Supervised Object Detection

2 code implementations CVPR 2022 Binbin Chen, WeiJie Chen, Shicai Yang, Yunyi Xuan, Jie Song, Di Xie, ShiLiang Pu, Mingli Song, Yueting Zhuang

To remedy this issue, we present a novel label assignment mechanism for self-training framework, namely proposal self-assignment, which injects the proposals from student into teacher and generates accurate pseudo labels to match each proposal in the student model accordingly.

object-detection Object Detection +1

Slimmable Domain Adaptation

2 code implementations CVPR 2022 Rang Meng, WeiJie Chen, Shicai Yang, Jie Song, Luojun Lin, Di Xie, ShiLiang Pu, Xinchao Wang, Mingli Song, Yueting Zhuang

In this paper, we introduce a simple framework, Slimmable Domain Adaptation, to improve cross-domain generalization with a weight-sharing model bank, from which models of different capacities can be sampled to accommodate different accuracy-efficiency trade-offs.

Domain Generalization Unsupervised Domain Adaptation

Transductive CLIP with Class-Conditional Contrastive Learning

no code implementations13 Jun 2022 Junchu Huang, WeiJie Chen, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang

This framework can reduce the impact of noisy labels from CLIP model effectively by combining both techniques.

Benchmark Contrastive Learning

Learning Domain Adaptive Object Detection with Probabilistic Teacher

1 code implementation13 Jun 2022 Meilin Chen, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Yunfeng Yan, Donglian Qi, Yueting Zhuang, Di Xie, ShiLiang Pu

In addition, we conduct anchor adaptation in parallel with localization adaptation, since anchor can be regarded as a learnable parameter.

object-detection Object Detection

Dynamic Domain Generalization

1 code implementation27 May 2022 Zhishu Sun, Zhifeng Shen, Luojun Lin, Yuanlong Yu, Zhifeng Yang, Shicai Yang, WeiJie Chen

Specifically, we leverage a meta-adjuster to twist the network parameters based on the static model with respect to different data from different domains.

Domain Generalization

Probing Simile Knowledge from Pre-trained Language Models

1 code implementation ACL 2022 WeiJie Chen, Yongzhu Chang, Rongsheng Zhang, Jiashu Pu, Guandan Chen, Le Zhang, Yadong Xi, Yijiang Chen, Chang Su

In this paper, we probe simile knowledge from PLMs to solve the SI and SG tasks in the unified framework of simile triple completion for the first time.

Language Modelling

Semi-Supervised Domain Generalization in Real World: New Benchmark and Strong Baseline

1 code implementation19 Nov 2021 Luojun Lin, Han Xie, Zhifeng Yang, Zhishu Sun, Wenxi Liu, Yuanlong Yu, WeiJie Chen, Shicai Yang, Di Xie

In this paper, we introduce a novel task, termed as semi-supervised domain generalization, to study how to interact the labeled and unlabeled domains, and establish two benchmarks including a web-crawled dataset, which poses a novel yet realistic challenge to push the limits of existing technologies.

Benchmark Domain Generalization

A Stochastic Composite Augmented Lagrangian Method For Reinforcement Learning

no code implementations20 May 2021 Yongfeng Li, Mingming Zhao, WeiJie Chen, Zaiwen Wen

A general theoretical analysis shows that the solutions generated from a sequence of the constrained optimizations converge to the optimal solution of the LP if the error is controlled properly.


Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation

no code implementations23 Feb 2021 WeiJie Chen, Luojun Lin, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang, Wenqi Ren

Usually, the given source domain pre-trained model is expected to optimize with only unlabeled target data, which is termed as source-free unsupervised domain adaptation.

Self-Supervised Learning Unsupervised Domain Adaptation

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

1 code implementation28 Oct 2019 Yuzhi Zhang, Haidi Wang, WeiJie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, Weinan E

Materials 3, 023804] and is capable of generating uniformly accurate deep learning based PES models in a way that minimizes human intervention and the computational cost for data generation and model training.

Computational Physics

Fast and Robust Rank Aggregation against Model Misspecification

no code implementations29 May 2019 Yuangang Pan, WeiJie Chen, Gang Niu, Ivor W. Tsang, Masashi Sugiyama

In rank aggregation, preferences from different users are summarized into a total order under the homogeneous data assumption.

Bayesian Inference

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