Search Results for author: Zichen Wang

Found 19 papers, 8 papers with code

Fine-Grained Prototypes Distillation for Few-Shot Object Detection

1 code implementation15 Jan 2024 Zichen Wang, Bo Yang, Haonan Yue, Zhenghao Ma

However, the class-level prototypes are difficult to precisely generate, and they also lack detailed information, leading to instability in performance. New methods are required to capture the distinctive local context for more robust novel object detection.

Few-Shot Object Detection Meta-Learning +3

UMG-CLIP: A Unified Multi-Granularity Vision Generalist for Open-World Understanding

no code implementations12 Jan 2024 Bowen Shi, Peisen Zhao, Zichen Wang, Yuhang Zhang, Yaoming Wang, Jin Li, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian, Xiaopeng Zhang

Vision-language foundation models, represented by Contrastive language-image pre-training (CLIP), have gained increasing attention for jointly understanding both vision and textual tasks.

Panoptic Segmentation Retrieval +1

Accurate Differential Operators for Hybrid Neural Fields

1 code implementation10 Dec 2023 Aditya Chetan, Guandao Yang, Zichen Wang, Steve Marschner, Bharath Hariharan

Yet in many applications like rendering and simulation, hybrid neural fields can cause noticeable and unreasonable artifacts.

Pure Exploration in Asynchronous Federated Bandits

no code implementations17 Oct 2023 Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang

We study the federated pure exploration problem of multi-armed bandits and linear bandits, where $M$ agents cooperatively identify the best arm via communicating with the central server.

Multi-Armed Bandits

BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs

1 code implementation5 Oct 2023 Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai

Foundation models (FMs) are able to leverage large volumes of unlabeled data to demonstrate superior performance across a wide range of tasks.

Cross-Modal Retrieval Domain Generalization +3

Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction

no code implementations2 Oct 2023 Omid Bazgir, Zichen Wang, Ji Won Park, Marc Hafner, James Lu

Additionally, we show that the graph encoder is able to effectively utilize multimodal data to enhance tumor predictions.

Graph Neural Prompting with Large Language Models

1 code implementation27 Sep 2023 Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu

While existing work has explored utilizing knowledge graphs (KGs) to enhance language modeling via joint training and customized model architectures, applying this to LLMs is problematic owing to their large number of parameters and high computational cost.

Knowledge Graphs Language Modelling +2

Understanding Divergent Framing of the Supreme Court Controversies: Social Media vs. News Outlets

no code implementations18 Sep 2023 Jinsheng Pan, Zichen Wang, Weihong Qi, Hanjia Lyu, Jiebo Luo

Understanding the framing of political issues is of paramount importance as it significantly shapes how individuals perceive, interpret, and engage with these matters.

Decision Making

Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines

no code implementations28 Mar 2023 Jinsheng Pan, Weihong Qi, Zichen Wang, Hanjia Lyu, Jiebo Luo

There is a broad consensus that news media outlets incorporate ideological biases in their news articles.

Computational Assessment of Hyperpartisanship in News Titles

no code implementations16 Jan 2023 Hanjia Lyu, Jinsheng Pan, Zichen Wang, Jiebo Luo

Through an analysis of the topic distribution, we find that societal issues gradually receive more attention from all media groups.

Active Learning Language Modelling

Training self-supervised peptide sequence models on artificially chopped proteins

no code implementations9 Nov 2022 Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala, Layne Price

In this paper, we propose a new peptide data augmentation scheme, where we train peptide language models on artificially constructed peptides that are small contiguous subsets of longer, wild-type proteins; we refer to the training peptides as "chopped proteins".

Data Augmentation Language Modelling +2

Variational Causal Inference

2 code implementations13 Sep 2022 Yulun Wu, Layne C. Price, Zichen Wang, Vassilis N. Ioannidis, Robert A. Barton, George Karypis

Estimating an individual's potential outcomes under counterfactual treatments is a challenging task for traditional causal inference and supervised learning approaches when the outcome is high-dimensional (e. g. gene expressions, impulse responses, human faces) and covariates are relatively limited.

Causal Inference counterfactual

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications

no code implementations17 Feb 2022 Kexin Ding, Mu Zhou, Zichen Wang, Qiao Liu, Corey W. Arnold, Shaoting Zhang, Dimitri N. Metaxas

Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales.

Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing

1 code implementation Bioinformatics, Volume 36, Issue Supplement_1 2020 Zichen Wang, Mu Zhou, Corey Arnold

Unlike conventional graph convolution networks always assuming the same node attributes in a global graph, our approach models interdomain information fusion with bipartite graph convolution operation.

Drug Discovery

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