Search Results for author: Yijie Chen

Found 6 papers, 4 papers with code

Beyond Binary Gender: Evaluating Gender-Inclusive Machine Translation with Ambiguous Attitude Words

1 code implementation23 Jul 2024 Yijie Chen, Yijin Liu, Fandong Meng, Jinan Xu, Yufeng Chen, Jie zhou

This study presents a benchmark AmbGIMT (Gender-Inclusive Machine Translation with Ambiguous attitude words), which assesses gender bias beyond binary gender.

Machine Translation Translation

Comments as Natural Logic Pivots: Improve Code Generation via Comment Perspective

1 code implementation11 Apr 2024 Yijie Chen, Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

In this paper, we suggest that code comments are the natural logic pivot between natural language and code language and propose using comments to boost the code generation ability of code LLMs.

Code Generation HumanEval

Improving Translation Faithfulness of Large Language Models via Augmenting Instructions

1 code implementation24 Aug 2023 Yijie Chen, Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

The experimental results demonstrate significant improvements in translation performance with SWIE based on BLOOMZ-3b, particularly in zero-shot and long text translations due to reduced instruction forgetting risk.

Instruction Following Machine Translation +2

MSRL: Distributed Reinforcement Learning with Dataflow Fragments

no code implementations3 Oct 2022 Huanzhou Zhu, Bo Zhao, Gang Chen, Weifeng Chen, Yijie Chen, Liang Shi, Yaodong Yang, Peter Pietzuch, Lei Chen

Yet, current distributed RL systems tie the definition of RL algorithms to their distributed execution: they hard-code particular distribution strategies and only accelerate specific parts of the computation (e. g. policy network updates) on GPU workers.

reinforcement-learning Reinforcement Learning +1

Deep Level Set for Box-supervised Instance Segmentation in Aerial Images

no code implementations7 Dec 2021 Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu

Instead of learning the pairwise affinity, the level set method with the carefully designed energy functions treats the object segmentation as curve evolution, which is able to accurately recover the object's boundaries and prevent the interference from the indistinguishable background and similar objects.

Box-supervised Instance Segmentation Segmentation +1

Oriented RepPoints for Aerial Object Detection

2 code implementations CVPR 2022 Wentong Li, Yijie Chen, Kaixuan Hu, Jianke Zhu

In contrast to the generic object, aerial targets are often non-axis aligned with arbitrary orientations having the cluttered surroundings.

Object Object Detection In Aerial Images +2

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