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20212025
most citedSelf-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning

27 citations · 71 across the 15 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.CL2023

MELA: Multilingual Evaluation of Linguistic Acceptability

Ziyin Zhang, Yikang Liu, Weifang Huang +3

In this work, we present the largest benchmark to date on linguistic acceptability: Multilingual Evaluation of Linguistic Acceptability -- MELA, with 46K samples covering 10 langua…

cs.CV2023★ 27 cited

Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning

Yinda Chen, Wei Huang, Shenglong Zhou +2

The performance of existing supervised neuron segmentation methods is highly dependent on the number of accurate annotations, especially when applied to large scale electron micros…

cs.CV2023★ 3 cited

Learning Multiscale Consistency for Self-supervised Electron Microscopy Instance Segmentation

Yinda Chen, Wei Huang, Xiaoyu Liu +3

Instance segmentation in electron microscopy (EM) volumes is tough due to complex shapes and sparse annotations. Self-supervised learning helps but still struggles with intricate v…

cs.CV2023

Domain Adaptive Synapse Detection with Weak Point Annotations

Qi Chen, Wei Huang, Yueyi Zhang +1

The development of learning-based methods has greatly improved the detection of synapses from electron microscopy (EM) images. However, training a model for each dataset is time-co…

cs.LG2023

Toward Transparent Sequence Models with Model-Based Tree Markov Model

Chan Hsu, Wei-Chun Huang, Jun-Ting Wu +2

In this study, we address the interpretability issue in complex, black-box Machine Learning models applied to sequence data. We introduce the Model-Based tree Hidden Semi-Markov Mo…

cs.CV2023★ 18 cited

Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation

Yinda Chen, Che Liu, Wei Huang +3

Vision-Language Pretraining (VLP) has demonstrated remarkable capabilities in learning visual representations from textual descriptions of images without annotations. Yet, effectiv…

eess.AS2023★ 2 cited

Why We Should Report the Details in Subjective Evaluation of TTS More Rigorously

Cheng-Han Chiang, Wei-Ping Huang, Hung-yi Lee

This paper emphasizes the importance of reporting experiment details in subjective evaluations and demonstrates how such details can significantly impact evaluation results in the…

cs.CL2023

Revisiting Acceptability Judgements

Hai Hu, Ziyin Zhang, Weifang Huang +7

In this work, we revisit linguistic acceptability in the context of large language models. We introduce CoLAC - Corpus of Linguistic Acceptability in Chinese, the first large-scale…