Search Results for author: Yuchen Zhou

Found 24 papers, 11 papers with code

Self-Supervised Contrastive Graph Clustering Network via Structural Information Fusion

no code implementations8 Aug 2024 Xiaoyang Ji, Yuchen Zhou, Haofu Yang, Shiyue Xu, Jiahao Li

Graph clustering, a classical task in graph learning, involves partitioning the nodes of a graph into distinct clusters.

Anomaly Detection Clustering +3

Point-SAM: Promptable 3D Segmentation Model for Point Clouds

1 code implementation25 Jun 2024 Yuchen Zhou, Jiayuan Gu, Tung Yen Chiang, Fanbo Xiang, Hao Su

The development of 2D foundation models for image segmentation has been significantly advanced by the Segment Anything Model (SAM).

Image Segmentation Segmentation +1

CLAP: Learning Transferable Binary Code Representations with Natural Language Supervision

2 code implementations26 Feb 2024 Hao Wang, Zeyu Gao, Chao Zhang, Zihan Sha, Mingyang Sun, Yuchen Zhou, Wenyu Zhu, Wenju Sun, Han Qiu, Xi Xiao

At the core, our approach boosts superior transfer learning capabilities by effectively aligning binary code with their semantics explanations (in natural language), resulting a model able to generate better embeddings for binary code.

Representation Learning Transfer Learning

How Far Have We Gone in Vulnerability Detection Using Large Language Models

1 code implementation21 Nov 2023 Zeyu Gao, Hao Wang, Yuchen Zhou, Wenyu Zhu, Chao Zhang

Given the significant successes of large language models (LLMs) in various tasks, there is growing anticipation of their efficacy in vulnerability detection.

Vulnerability Detection

Divergences between Language Models and Human Brains

1 code implementation15 Nov 2023 Yuchen Zhou, Emmy Liu, Graham Neubig, Michael J. Tarr, Leila Wehbe

In this work, we systematically explore the divergences between human and machine language processing by examining the differences between LM representations and human brain responses to language as measured by Magnetoencephalography (MEG) across two datasets in which subjects read and listened to narrative stories.

Emotional Intelligence

Heteroskedastic Tensor Clustering

no code implementations4 Nov 2023 Yuchen Zhou, Yuxin Chen

Tensor clustering, which seeks to extract underlying cluster structures from noisy tensor observations, has gained increasing attention.

Clustering

Grounding Visual Illusions in Language: Do Vision-Language Models Perceive Illusions Like Humans?

1 code implementation31 Oct 2023 Yichi Zhang, Jiayi Pan, Yuchen Zhou, Rui Pan, Joyce Chai

Vision-Language Models (VLMs) are trained on vast amounts of data captured by humans emulating our understanding of the world.

Efficiently Visualizing Large Graphs

1 code implementation17 Oct 2023 Xinyu Li, Yao Xiao, Yuchen Zhou

Performing SPLEE to obtain a high-dimensional embedding of the large-scale graph and then using t-SGNE to reduce its dimension for visualization, we are able to visualize graphs with up to 300K nodes and 1M edges within 5 minutes and achieve approximately 10% improvement in visualization quality.

Dimensionality Reduction Graph Embedding

kTrans: Knowledge-Aware Transformer for Binary Code Embedding

1 code implementation24 Aug 2023 Wenyu Zhu, Hao Wang, Yuchen Zhou, JiaMing Wang, Zihan Sha, Zeyu Gao, Chao Zhang

By feeding explicit knowledge as additional inputs to the Transformer, and fusing implicit knowledge with a novel pre-training task, kTrans provides a new perspective to incorporating domain knowledge into a Transformer framework.

Outlier Detection

Quantifying the Roles of Visual, Linguistic, and Visual-Linguistic Complexity in Verb Acquisition

1 code implementation5 Apr 2023 Yuchen Zhou, Michael J. Tarr, Daniel Yurovsky

Based on these results, we conclude that verb acquisition is influenced by all three sources of complexity, but that the variability of visual structure poses the most significant challenge for verb learning.

Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA

no code implementations10 Mar 2023 Yuchen Zhou, Yuxin Chen

This paper is concerned with estimating the column subspace of a low-rank matrix $\boldsymbol{X}^\star \in \mathbb{R}^{n_1\times n_2}$ from contaminated data.

Deep Differential Amplifier for Extractive Summarization

no code implementations ACL 2021 Ruipeng Jia, Yanan Cao, Fang Fang, Yuchen Zhou, Zheng Fang, Yanbing Liu, Shi Wang

In this paper, we conceptualize the single-document extractive summarization as a rebalance problem and present a deep differential amplifier framework.

Extractive Summarization imbalanced classification +1

Inference for Low-rank Tensors -- No Need to Debias

no code implementations29 Dec 2020 Dong Xia, Anru R. Zhang, Yuchen Zhou

In all these models, we observe that different from many matrix/vector settings in existing work, debiasing is not required to establish the asymptotic distribution of estimates or to make statistical inference on low-rank tensors.

regression

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation

no code implementations NeurIPS 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep K. Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation

no code implementations30 Oct 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference

no code implementations21 Sep 2019 T. Tony Cai, Anru R. Zhang, Yuchen Zhou

We study sparse group Lasso for high-dimensional double sparse linear regression, where the parameter of interest is simultaneously element-wise and group-wise sparse.

regression

On the Non-asymptotic and Sharp Lower Tail Bounds of Random Variables

no code implementations21 Oct 2018 Anru R. Zhang, Yuchen Zhou

The non-asymptotic tail bounds of random variables play crucial roles in probability, statistics, and machine learning.

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