Search Results for author: Ying Zhang

Found 167 papers, 69 papers with code

Improving Zero-Shot Entity Linking Candidate Generation with Ultra-Fine Entity Type Information

1 code implementation COLING 2022 Xuhui Sui, Ying Zhang, Kehui Song, Baohang Zhou, Guoqing Zhao, Xin Wei, Xiaojie Yuan

Recently, zero-shot entity linking task has become a research hotspot, which links mentions to unseen entities to challenge the generalization ability.

Entity Linking Entity Typing +1

ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation Models

1 code implementation5 Feb 2025 Ying Zhang, Maoliang Yin, Wenfu Bi, Haibao Yan, Shaohan Bian, Cui-Hua Zhang, Changchun Hua

Service robots operating in unstructured environments must effectively recognize and segment unknown objects to enhance their functionality.

Object Segmentation +2

Data and System Perspectives of Sustainable Artificial Intelligence

no code implementations13 Jan 2025 Tao Xie, David Harel, Dezhi Ran, Zhenwen Li, Maoliang Li, Zhi Yang, Leye Wang, Xiang Chen, Ying Zhang, Wentao Zhang, Meng Li, Chen Zhang, Linyi Li, Assaf Marron

Sustainable AI is a subfield of AI for concerning developing and using AI systems in ways of aiming to reduce environmental impact and achieve sustainability.

mFabric: An Efficient and Scalable Fabric for Mixture-of-Experts Training

no code implementations7 Jan 2025 Xudong Liao, Yijun Sun, Han Tian, Xinchen Wan, Yilun Jin, Zilong Wang, Zhenghang Ren, Xinyang Huang, Wenxue Li, Kin Fai Tse, Zhizhen Zhong, Guyue Liu, Ying Zhang, Xiaofeng Ye, Yiming Zhang, Kai Chen

Mixture-of-Expert (MoE) models outperform conventional models by selectively activating different subnets, named \emph{experts}, on a per-token basis.

Blocking

Generalization-Enhanced Few-Shot Object Detection in Remote Sensing

1 code implementation5 Jan 2025 Hui Lin, Nan Li, Pengjuan Yao, Kexin Dong, Yuhan Guo, Danfeng Hong, Ying Zhang, Congcong Wen

However, the generalization capability of FSOD models, particularly in remote sensing, is often constrained by the complex and diverse characteristics of the objects present in such environments.

Few-Shot Learning Few-Shot Object Detection +3

On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing

1 code implementation4 Jan 2025 Jianwei Wang, Kai Wang, Ying Zhang, Wenjie Zhang, Xiwei Xu, Xuemin Lin

Missing data imputation, which aims to impute the missing values in the raw datasets to achieve the completeness of datasets, is crucial for modern data-driven models like large language models (LLMs) and has attracted increasing interest over the past decades.

Chunking Imputation +1

Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales

1 code implementation24 Dec 2024 Xinyu Yang, Yu Sun, Xinyang Chen, Ying Zhang, Xiaojie Yuan

Spatial-temporal data collected across different geographic locations often suffer from missing values, posing challenges to data analysis.

Graph structure learning Imputation +2

FedCross: Intertemporal Federated Learning Under Evolutionary Games

no code implementations22 Dec 2024 Jianfeng Lu, Ying Zhang, Riheng Jia, Shuqin Cao, Jing Liu, Hao Fu

Federated Learning (FL) mitigates privacy leakage in decentralized machine learning by allowing multiple clients to train collaboratively locally.

Federated Learning

Trusted Mamba Contrastive Network for Multi-View Clustering

1 code implementation21 Dec 2024 Jian Zhu, Xin Zou, Lei Liu, Zhangmin Huang, Ying Zhang, Chang Tang, Li-Rong Dai

The reasons for this problem are as follows: 1) The current methods ignore the presence of noise or redundant information in the view; 2) The similarity of contrastive learning comes from the same sample rather than the same cluster in deep multi-view clustering.

Clustering Contrastive Learning +1

Efficient Dynamic Attributed Graph Generation

no code implementations11 Dec 2024 Fan Li, Xiaoyang Wang, Dawei Cheng, Cong Chen, Ying Zhang, Xuemin Lin

iii) Current state-of-the-art dynamic graph generators are based on the temporal random walk, making the simulation process time-consuming.

Attribute Graph Generation

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

1 code implementation22 Nov 2024 Bencheng Liao, Shaoyu Chen, Haoran Yin, Bo Jiang, Cheng Wang, Sixu Yan, Xinbang Zhang, Xiangyu Li, Ying Zhang, Qian Zhang, Xinggang Wang

However, the numerous denoising steps in the robotic diffusion policy and the more dynamic, open-world nature of traffic scenes pose substantial challenges for generating diverse driving actions at a real-time speed.

Autonomous Driving Denoising

Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection

no code implementations18 Nov 2024 Jikang Cheng, Zhiyuan Yan, Ying Zhang, Li Hao, Jiaxin Ai, Qin Zou, Chen Li, Zhongyuan Wang

Incremental Face Forgery Detection (IFFD), involving gradually adding new forgery data to fine-tune the previously trained model, has been introduced as a promising strategy to deal with evolving forgery methods.

Specificity

Domain Generalization for Cross-Receiver Radio Frequency Fingerprint Identification

no code implementations6 Nov 2024 Ying Zhang, Qiang Li, Hongli Liu, Liu Yang, Jian Yang

Radio Frequency Fingerprint Identification (RFFI) technology uniquely identifies emitters by analyzing unique distortions in the transmitted signal caused by non-ideal hardware.

Domain Generalization Federated Learning

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation

1 code implementation4 Nov 2024 Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas Sridharan, Ying Zhang, Tushar Krishna, Pan Li

By interpreting the partial order of nodes as a sequence of bipartite graphs, LayerDAG leverages autoregressive generation to model directional dependencies and employs diffusion models to capture logical dependencies within each bipartite graph.

Benchmarking Graph Generation

FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs

no code implementations22 Oct 2024 Haoran Lin, Xianzhi Yu, Kang Zhao, Lu Hou, Zongyuan Zhan, Stanislav Kamenev, Han Bao, Ting Hu, Mingkai Wang, Qixin Chang, Siyue Sui, Weihao Sun, Jiaxin Hu, Jun Yao, Zekun Yin, Cheng Qian, Ying Zhang, Yinfei Pan, Yu Yang, Weiguo Liu

In this work, we propose FastAttention which pioneers the adaptation of FlashAttention series for NPUs and low-resource GPUs to boost LLM inference efficiency.

GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric Learning

1 code implementation20 Oct 2024 Haiwen Diao, Ying Zhang, Shang Gao, Jiawen Zhu, Long Chen, Huchuan Lu

Cross-modal metric learning is a prominent research topic that bridges the semantic heterogeneity between vision and language.

Image Retrieval Image-text Retrieval +4

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning

no code implementations15 Oct 2024 Guangxin Su, Yifan Zhu, Wenjie Zhang, Hanchen Wang, Ying Zhang

In this paper, we introduce LangGSL, a robust framework that integrates the complementary strengths of pre-trained language models and GSLMs to jointly enhance both node feature and graph structure learning.

Graph Representation Learning Graph structure learning

CLIP-SCGI: Synthesized Caption-Guided Inversion for Person Re-Identification

no code implementations12 Oct 2024 Qianru Han, Xinwei He, Zhi Liu, Sannyuya Liu, Ying Zhang, Jinhai Xiang

To address quality issues in generated captions, we introduce a caption-guided inversion module that captures semantic attributes from images by converting relevant visual information into pseudo-word tokens based on the descriptions.

Image Captioning Person Re-Identification

TCGU: Data-centric Graph Unlearning based on Transferable Condensation

no code implementations9 Oct 2024 Fan Li, Xiaoyang Wang, Dawei Cheng, Wenjie Zhang, Ying Zhang, Xuemin Lin

With growing demands for data privacy and model robustness, graph unlearning (GU), which erases the influence of specific data on trained GNN models, has gained significant attention.

Exploring LLM-based Data Annotation Strategies for Medical Dialogue Preference Alignment

no code implementations5 Oct 2024 Chengfeng Dou, Ying Zhang, Zhi Jin, Wenpin Jiao, Haiyan Zhao, Yongqiang Zhao, Zhengwei Tao

We argue that the primary challenges in current RLAIF research for healthcare are the limitations of automated evaluation methods and the difficulties in accurately representing physician preferences.

AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking

no code implementations26 Sep 2024 Shiqi Sun, Yantao Lu, Ning Liu, Bo Jiang, Jinchao Chen, Ying Zhang

The redundant parameters can be pruned by our proposed importance score evaluation function, Alternative Evaluation (AlterEva), which is based on the observation of the loss changes when certain modality parameters are activated and deactivated.

Autonomous Driving

Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks

1 code implementation25 Sep 2024 Luxu Liang, Ariel Neufeld, Ying Zhang

In this paper, we provide a non-asymptotic analysis of the convergence of the stochastic gradient Hamiltonian Monte Carlo (SGHMC) algorithm to a target measure in Wasserstein-1 and Wasserstein-2 distance.

Stochastic Optimization

Edge Modeling Activation Free Fourier Network for Spacecraft Image Denoising

no code implementations11 Sep 2024 Jingfan Yang, Hu Gao, Ying Zhang, Bowen Ma, Depeng Dang

We present AFFB and utilize an improved fast fourier block to extract repetitive periodic features and long-range information in noisy spacecraft image.

Image Denoising

Can We Leave Deepfake Data Behind in Training Deepfake Detector?

no code implementations30 Aug 2024 Jikang Cheng, Zhiyuan Yan, Ying Zhang, Yuhao Luo, Zhongyuan Wang, Chen Li

The accumulation of forgery information should be oriented and progressively increasing during this transition process.

Face Swapping

First Activations Matter: Training-Free Methods for Dynamic Activation in Large Language Models

no code implementations21 Aug 2024 Chi Ma, Mincong Huang, Ying Zhang, Chao Wang, Yujie Wang, Lei Yu, Chuan Liu, Wei Lin

Dynamic activation (DA) techniques, such as DejaVu and MoEfication, have demonstrated their potential to significantly enhance the inference efficiency of large language models (LLMs).

ED$^4$: Explicit Data-level Debiasing for Deepfake Detection

no code implementations13 Aug 2024 Jikang Cheng, Ying Zhang, Qin Zou, Zhiyuan Yan, Chao Liang, Zhongyuan Wang, Chen Li

Learning intrinsic bias from limited data has been considered the main reason for the failure of deepfake detection with generalizability.

DeepFake Detection Disentanglement +1

DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs

no code implementations13 Aug 2024 Dongyuan Li, Shiyin Tan, Ying Zhang, Ming Jin, Shirui Pan, Manabu Okumura, Renhe Jiang

Dynamic graph learning aims to uncover evolutionary laws in real-world systems, enabling accurate social recommendation (link prediction) or early detection of cancer cells (classification).

Dynamic Link Prediction Dynamic Node Classification +5

DePatch: Towards Robust Adversarial Patch for Evading Person Detectors in the Real World

no code implementations13 Aug 2024 Jikang Cheng, Ying Zhang, Zhongyuan Wang, Zou Qin, Chen Li

Recent years have seen an increasing interest in physical adversarial attacks, which aim to craft deployable patterns for deceiving deep neural networks, especially for person detectors.

Reconsidering Degeneration of Token Embeddings with Definitions for Encoder-based Pre-trained Language Models

no code implementations2 Aug 2024 Ying Zhang, Dongyuan Li, Manabu Okumura

Learning token embeddings based on token co-occurrence statistics has proven effective for both pre-training and fine-tuning in natural language processing.

Text Summarization

The Llama 3 Herd of Models

2 code implementations31 Jul 2024 Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurelien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Roziere, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, Danny Wyatt, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Francisco Guzmán, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Govind Thattai, Graeme Nail, Gregoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel Kloumann, Ishan Misra, Ivan Evtimov, Jack Zhang, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer Van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Karthik Prasad, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, Khalid El-Arini, Krithika Iyer, Kshitiz Malik, Kuenley Chiu, Kunal Bhalla, Kushal Lakhotia, Lauren Rantala-Yeary, Laurens van der Maaten, Lawrence Chen, Liang Tan, Liz Jenkins, Louis Martin, Lovish Madaan, Lubo Malo, Lukas Blecher, Lukas Landzaat, Luke de Oliveira, Madeline Muzzi, Mahesh Pasupuleti, Mannat Singh, Manohar Paluri, Marcin Kardas, Maria Tsimpoukelli, Mathew Oldham, Mathieu Rita, Maya Pavlova, Melanie Kambadur, Mike Lewis, Min Si, Mitesh Kumar Singh, Mona Hassan, Naman Goyal, Narjes Torabi, Nikolay Bashlykov, Nikolay Bogoychev, Niladri Chatterji, Ning Zhang, Olivier Duchenne, Onur Çelebi, Patrick Alrassy, Pengchuan Zhang, Pengwei Li, Petar Vasic, Peter Weng, Prajjwal Bhargava, Pratik Dubal, Praveen Krishnan, Punit Singh Koura, Puxin Xu, Qing He, Qingxiao Dong, Ragavan Srinivasan, Raj Ganapathy, Ramon Calderer, Ricardo Silveira Cabral, Robert Stojnic, Roberta Raileanu, Rohan Maheswari, Rohit Girdhar, Rohit Patel, Romain Sauvestre, Ronnie Polidoro, Roshan Sumbaly, Ross Taylor, Ruan Silva, Rui Hou, Rui Wang, Saghar Hosseini, Sahana Chennabasappa, Sanjay Singh, Sean Bell, Seohyun Sonia Kim, Sergey Edunov, Shaoliang Nie, Sharan Narang, Sharath Raparthy, Sheng Shen, Shengye Wan, Shruti Bhosale, Shun Zhang, Simon Vandenhende, Soumya Batra, Spencer Whitman, Sten Sootla, Stephane Collot, Suchin Gururangan, Sydney Borodinsky, Tamar Herman, Tara Fowler, Tarek Sheasha, Thomas Georgiou, Thomas Scialom, Tobias Speckbacher, Todor Mihaylov, Tong Xiao, Ujjwal Karn, Vedanuj Goswami, Vibhor Gupta, Vignesh Ramanathan, Viktor Kerkez, Vincent Gonguet, Virginie Do, Vish Vogeti, Vítor Albiero, Vladan Petrovic, Weiwei Chu, Wenhan Xiong, Wenyin Fu, Whitney Meers, Xavier Martinet, Xiaodong Wang, Xiaofang Wang, Xiaoqing Ellen Tan, Xide Xia, Xinfeng Xie, Xuchao Jia, Xuewei Wang, Yaelle Goldschlag, Yashesh Gaur, Yasmine Babaei, Yi Wen, Yiwen Song, Yuchen Zhang, Yue Li, Yuning Mao, Zacharie Delpierre Coudert, Zheng Yan, Zhengxing Chen, Zoe Papakipos, Aaditya Singh, Aayushi Srivastava, Abha Jain, Adam Kelsey, Adam Shajnfeld, Adithya Gangidi, Adolfo Victoria, Ahuva Goldstand, Ajay Menon, Ajay Sharma, Alex Boesenberg, Alexei Baevski, Allie Feinstein, Amanda Kallet, Amit Sangani, Amos Teo, Anam Yunus, Andrei Lupu, Andres Alvarado, Andrew Caples, Andrew Gu, Andrew Ho, Andrew Poulton, Andrew Ryan, Ankit Ramchandani, Annie Dong, Annie Franco, Anuj Goyal, Aparajita Saraf, Arkabandhu Chowdhury, Ashley Gabriel, Ashwin Bharambe, Assaf Eisenman, Azadeh Yazdan, Beau James, Ben Maurer, Benjamin Leonhardi, Bernie Huang, Beth Loyd, Beto De Paola, Bhargavi Paranjape, Bing Liu, Bo Wu, Boyu Ni, Braden Hancock, Bram Wasti, Brandon Spence, Brani Stojkovic, Brian Gamido, Britt Montalvo, Carl Parker, Carly Burton, Catalina Mejia, Ce Liu, Changhan Wang, Changkyu Kim, Chao Zhou, Chester Hu, Ching-Hsiang Chu, Chris Cai, Chris Tindal, Christoph Feichtenhofer, Cynthia Gao, Damon Civin, Dana Beaty, Daniel Kreymer, Daniel Li, David Adkins, David Xu, Davide Testuggine, Delia David, Devi Parikh, Diana Liskovich, Didem Foss, Dingkang Wang, Duc Le, Dustin Holland, Edward Dowling, Eissa Jamil, Elaine Montgomery, Eleonora Presani, Emily Hahn, Emily Wood, Eric-Tuan Le, Erik Brinkman, Esteban Arcaute, Evan Dunbar, Evan Smothers, Fei Sun, Felix Kreuk, Feng Tian, Filippos Kokkinos, Firat Ozgenel, Francesco Caggioni, Frank Kanayet, Frank Seide, Gabriela Medina Florez, Gabriella Schwarz, Gada Badeer, Georgia Swee, Gil Halpern, Grant Herman, Grigory Sizov, Guangyi, Zhang, Guna Lakshminarayanan, Hakan Inan, Hamid Shojanazeri, Han Zou, Hannah Wang, Hanwen Zha, Haroun Habeeb, Harrison Rudolph, Helen Suk, Henry Aspegren, Hunter Goldman, Hongyuan Zhan, Ibrahim Damlaj, Igor Molybog, Igor Tufanov, Ilias Leontiadis, Irina-Elena Veliche, Itai Gat, Jake Weissman, James Geboski, James Kohli, Janice Lam, Japhet Asher, Jean-Baptiste Gaya, Jeff Marcus, Jeff Tang, Jennifer Chan, Jenny Zhen, Jeremy Reizenstein, Jeremy Teboul, Jessica Zhong, Jian Jin, Jingyi Yang, Joe Cummings, Jon Carvill, Jon Shepard, Jonathan McPhie, Jonathan Torres, Josh Ginsburg, Junjie Wang, Kai Wu, Kam Hou U, Karan Saxena, Kartikay Khandelwal, Katayoun Zand, Kathy Matosich, Kaushik Veeraraghavan, Kelly Michelena, Keqian Li, Kiran Jagadeesh, Kun Huang, Kunal Chawla, Kyle Huang, Lailin Chen, Lakshya Garg, Lavender A, Leandro Silva, Lee Bell, Lei Zhang, Liangpeng Guo, Licheng Yu, Liron Moshkovich, Luca Wehrstedt, Madian Khabsa, Manav Avalani, Manish Bhatt, Martynas Mankus, Matan Hasson, Matthew Lennie, Matthias Reso, Maxim Groshev, Maxim Naumov, Maya Lathi, Meghan Keneally, Miao Liu, Michael L. Seltzer, Michal Valko, Michelle Restrepo, Mihir Patel, Mik Vyatskov, Mikayel Samvelyan, Mike Clark, Mike Macey, Mike Wang, Miquel Jubert Hermoso, Mo Metanat, Mohammad Rastegari, Munish Bansal, Nandhini Santhanam, Natascha Parks, Natasha White, Navyata Bawa, Nayan Singhal, Nick Egebo, Nicolas Usunier, Nikhil Mehta, Nikolay Pavlovich Laptev, Ning Dong, Norman Cheng, Oleg Chernoguz, Olivia Hart, Omkar Salpekar, Ozlem Kalinli, Parkin Kent, Parth Parekh, Paul Saab, Pavan Balaji, Pedro Rittner, Philip Bontrager, Pierre Roux, Piotr Dollar, Polina Zvyagina, Prashant Ratanchandani, Pritish Yuvraj, Qian Liang, Rachad Alao, Rachel Rodriguez, Rafi Ayub, Raghotham Murthy, Raghu Nayani, Rahul Mitra, Rangaprabhu Parthasarathy, Raymond Li, Rebekkah Hogan, Robin Battey, Rocky Wang, Russ Howes, Ruty Rinott, Sachin Mehta, Sachin Siby, Sai Jayesh Bondu, Samyak Datta, Sara Chugh, Sara Hunt, Sargun Dhillon, Sasha Sidorov, Satadru Pan, Saurabh Mahajan, Saurabh Verma, Seiji Yamamoto, Sharadh Ramaswamy, Shaun Lindsay, Sheng Feng, Shenghao Lin, Shengxin Cindy Zha, Shishir Patil, Shiva Shankar, Shuqiang Zhang, Sinong Wang, Sneha Agarwal, Soji Sajuyigbe, Soumith Chintala, Stephanie Max, Stephen Chen, Steve Kehoe, Steve Satterfield, Sudarshan Govindaprasad, Sumit Gupta, Summer Deng, Sungmin Cho, Sunny Virk, Suraj Subramanian, Sy Choudhury, Sydney Goldman, Tal Remez, Tamar Glaser, Tamara Best, Thilo Koehler, Thomas Robinson, Tianhe Li, Tianjun Zhang, Tim Matthews, Timothy Chou, Tzook Shaked, Varun Vontimitta, Victoria Ajayi, Victoria Montanez, Vijai Mohan, Vinay Satish Kumar, Vishal Mangla, Vlad Ionescu, Vlad Poenaru, Vlad Tiberiu Mihailescu, Vladimir Ivanov, Wei Li, Wenchen Wang, WenWen Jiang, Wes Bouaziz, Will Constable, Xiaocheng Tang, Xiaojian Wu, Xiaolan Wang, Xilun Wu, Xinbo Gao, Yaniv Kleinman, Yanjun Chen, Ye Hu, Ye Jia, Ye Qi, Yenda Li, Yilin Zhang, Ying Zhang, Yossi Adi, Youngjin Nam, Yu, Wang, Yu Zhao, Yuchen Hao, Yundi Qian, Yunlu Li, Yuzi He, Zach Rait, Zachary DeVito, Zef Rosnbrick, Zhaoduo Wen, Zhenyu Yang, Zhiwei Zhao, Zhiyu Ma

This paper presents a new set of foundation models, called Llama 3.

Ranked #3 on Multi-task Language Understanding on MMLU (using extra training data)

Language Modeling Language Modelling +3

Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method

no code implementations27 Jul 2024 Sungjoo Chung, Ying Zhang, Zhaoyu Wang, Fei Ding

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation.

Computational Efficiency regression

RIDA: A Robust Attack Framework on Incomplete Graphs

no code implementations25 Jul 2024 Jianke Yu, Hanchen Wang, Chen Chen, Xiaoyang Wang, Lu Qin, Wenjie Zhang, Ying Zhang, Xijuan Liu

However, current research overlooks the real-world scenario of incomplete graphs. To address this gap, we introduce the Robust Incomplete Deep Attack Framework (RIDA).

FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

1 code implementation11 Jul 2024 Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao

Attention, as a core layer of the ubiquitous Transformer architecture, is the bottleneck for large language models and long-context applications.

Quantization

SHERL: Synthesizing High Accuracy and Efficient Memory for Resource-Limited Transfer Learning

1 code implementation10 Jul 2024 Haiwen Diao, Bo Wan, Xu Jia, Yunzhi Zhuge, Ying Zhang, Huchuan Lu, Long Chen

Parameter-efficient transfer learning (PETL) has emerged as a flourishing research field for adapting large pre-trained models to downstream tasks, greatly reducing trainable parameters while grappling with memory challenges during fine-tuning.

Transfer Learning

CryptoGPT: a 7B model rivaling GPT-4 in the task of analyzing and classifying real-time financial news

no code implementations20 Jun 2024 Ying Zhang, Matthieu Petit Guillaume, Aurélien Krauth, Manel Labidi

CryptoGPT: a 7B model competing with GPT-4 in a specific task -- The Impact of Automatic Annotation and Strategic Fine-Tuning via QLoRAIn this article, we present a method aimed at refining a dedicated LLM of reasonable quality with limited resources in an industrial setting via CryptoGPT.

Paths of A Million People: Extracting Life Trajectories from Wikipedia

1 code implementation25 May 2024 Ying Zhang, Xiaofeng Li, Zhaoyang Liu, Haipeng Zhang

The life trajectories of notable people have been studied to pinpoint the times and places of significant events such as birth, death, education, marriage, competition, work, speeches, scientific discoveries, artistic achievements, and battles.

Contrastive Learning Human Dynamics

Emphasizing Crucial Features for Efficient Image Restoration

1 code implementation19 May 2024 Hu Gao, Bowen Ma, Ying Zhang, Jingfan Yang, Jing Yang, Depeng Dang

SFAM consists of two modules: the spatial domain attention module (SDAM) and the frequency domain attention module (FDAM).

Image Restoration

Edge Computing for IoT: Novel Insights from a Comparative Analysis of Access Control Models

no code implementations13 May 2024 Tao Xue, Ying Zhang, Yanbin Wang, Wenbo Wang, Shuailou Li, Haibin Zhang

IoT edge computing positions computing resources closer to the data sources to reduce the latency, relieve the bandwidth pressure on the cloud, and enhance data security.

Autonomous Vehicles Cloud Computing +1

Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms

no code implementations9 May 2024 Ariel Neufeld, Ying Zhang

We establish non-asymptotic convergence bounds for aHOLA in Wasserstein-1 and Wasserstein-2 distances with rates of convergence equal to $1+q/2$ and $1/2+q/4$, respectively, under a local H\"{o}lder condition with exponent $q\in(0, 1]$ and a convexity at infinity condition on the potential of the target distribution.

Community-Invariant Graph Contrastive Learning

1 code implementation2 May 2024 Shiyin Tan, Dongyuan Li, Renhe Jiang, Ying Zhang, Manabu Okumura

Graph augmentation has received great attention in recent years for graph contrastive learning (GCL) to learn well-generalized node/graph representations.

Contrastive Learning

Active Learning with Task Adaptation Pre-training for Speech Emotion Recognition

no code implementations1 May 2024 Dongyuan Li, Ying Zhang, Yusong Wang, Funakoshi Kataro, Manabu Okumura

To address these issues, we propose an active learning (AL)-based fine-tuning framework for SER, called \textsc{After}, that leverages task adaptation pre-training (TAPT) and AL methods to enhance performance and efficiency.

Active Learning Speech Emotion Recognition +2

Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching

1 code implementation28 Apr 2024 Haiwen Diao, Ying Zhang, Shang Gao, Xiang Ruan, Huchuan Lu

Specifically, we propose a brand-new Deep Boosting Learning (DBL) algorithm, where an anchor branch is first trained to provide insights into the data properties, with a target branch gaining more advanced knowledge to develop optimal features and distance metrics.

Contrastive Learning Image-text matching +2

UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation

no code implementations22 Apr 2024 Siru Zhong, Xixuan Hao, Yibo Yan, Ying Zhang, Yangqiu Song, Yuxuan Liang

Urbanization challenges underscore the necessity for effective satellite image-text retrieval methods to swiftly access specific information enriched with geographic semantics for urban applications.

Diversity Domain Adaptation +2

Hypergraph Self-supervised Learning with Sampling-efficient Signals

1 code implementation18 Apr 2024 Fan Li, Xiaoyang Wang, Dawei Cheng, Wenjie Zhang, Ying Zhang, Xuemin Lin

Self-supervised learning (SSL) provides a promising alternative for representation learning on hypergraphs without costly labels.

Representation Learning Self-Supervised Learning

Mumpy: Multilateral Temporal-view Pyramid Transformer for Video Inpainting Detection

no code implementations17 Apr 2024 Ying Zhang, Yuezun Li, Bo Peng, Jiaran Zhou, Huiyu Zhou, Junyu Dong

The task of video inpainting detection is to expose the pixel-level inpainted regions within a video sequence.

Decoder Diversity +1

Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection

no code implementations15 Apr 2024 Yuxi Li, Yi Liu, Gelei Deng, Ying Zhang, Wenjia Song, Ling Shi, Kailong Wang, Yuekang Li, Yang Liu, Haoyu Wang

We present categorizations of the identified glitch tokens and symptoms exhibited by LLMs when interacting with glitch tokens.

FIT-RAG: Black-Box RAG with Factual Information and Token Reduction

no code implementations21 Mar 2024 YUREN MAO, XueMei Dong, Wenyi Xu, Yunjun Gao, Bin Wei, Ying Zhang

Simply concatenating all the retrieved documents brings large amounts of unnecessary tokens for LLMs, which degenerates the efficiency of black-box RAG.

Open-Domain Question Answering RAG +3

Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation

1 code implementation17 Mar 2024 Tianhao Huang, Xuan Pan, Xiangrui Cai, Ying Zhang, Xiaojie Yuan

The comprehensive experimental results demonstrate the superiority of MTNet over ten state-of-the-art next POI recommendation models across three real-world LBSN datasets, substantiating the efficacy of time slot preference learning facilitated by Mobility Tree.

point of interests

LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection

1 code implementation14 Mar 2024 Xiangrui Cai, Yang Wang, Sihan Xu, Hao Li, Ying Zhang, Zheli Liu, Xiaojie Yuan

Moreover, LAN can be also applied to post-hoc ITD, surpassing 8 competitive baselines by at least 7. 70% and 4. 03% in AUC on two datasets.

Anomaly Detection Graph structure learning

RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models

no code implementations11 Mar 2024 Liangliang Chen, Yutian Lei, Shiyu Jin, Ying Zhang, Liangjun Zhang

In this paper, we propose RLingua, a framework that can leverage the internal knowledge of large language models (LLMs) to reduce the sample complexity of RL in robotic manipulations.

Prompt Engineering Reinforcement Learning (RL)

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates

no code implementations22 Nov 2023 Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis

As a result, we obtain the best known upper bound estimates in terms of key quantities of interest, such as the dimension and rates of convergence, for the Wasserstein-2 distance between the data distribution (Gaussian with unknown mean) and our sampling algorithm.

Modelling the Formation of Peer-to-Peer Trading Coalitions and Prosumer Participation Incentives in Transactive Energy Communities

no code implementations19 Nov 2023 Ying Zhang, Valentin Robu, Sho Cremers, Sonam Norbu, Benoit Couraud, Merlinda Andoni, David Flynn, H. Vincent Poor

Our experimental study shows that, for both market models, only a small number of P2P contracts, and only a fraction of total prosumers in the community are required to achieve the majority of the maximal potential Gains from Trade.

Diversity energy trading

Cooperative Multi-Agent Deep Reinforcement Learning for Adaptive Decentralized Emergency Voltage Control

no code implementations20 Oct 2023 Ying Zhang, Meng Yue

Under voltage load shedding (UVLS) for power grid emergency control builds the last defensive perimeter to prevent cascade outages and blackouts in case of contingencies.

Deep Reinforcement Learning reinforcement-learning

A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud

no code implementations30 Sep 2023 Wenjie Liu, Ying Zhang, Zhiliang Deng, Jiaojiao Zhao, Lian Tong

In order to solve these problems, a hybrid quantum-classical conditional generative adversarial network (QCGAN) algorithm is proposed, which is a knowledge-driven human-computer interaction computing mode that can be implemented in cloud.

Cloud Computing Generative Adversarial Network +1

High-Fidelity Speech Synthesis with Minimal Supervision: All Using Diffusion Models

no code implementations27 Sep 2023 Chunyu Qiang, Hao Li, Yixin Tian, Yi Zhao, Ying Zhang, Longbiao Wang, Jianwu Dang

To address these issues, we propose a minimally-supervised high-fidelity speech synthesis method, where all modules are constructed based on the diffusion models.

Speech Synthesis Text to Speech +1

pLMFPPred: a novel approach for accurate prediction of functional peptides integrating embedding from pre-trained protein language model and imbalanced learning

no code implementations25 Sep 2023 Zebin Ma, Yonglin Zou, Xiaobin Huang, Wenjin Yan, Hao Xu, Jiexin Yang, Ying Zhang, Jinqi Huang

Comparative experiments show that pLMFPPred outperforms current methods for predicting functional peptides. The experimental results suggest that the proposed method (pLMFPPred) can provide better performance in terms of Accuracy, Area under the curve - Receiver Operating Characteristics, and F1-Score than existing methods.

feature selection Language Modeling +1

UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory

1 code implementation CVPR 2024 Haiwen Diao, Bo Wan, Ying Zhang, Xu Jia, Huchuan Lu, Long Chen

Parameter-efficient transfer learning (PETL), i. e., fine-tuning a small portion of parameters, is an effective strategy for adapting pre-trained models to downstream domains.

Question Answering Text Retrieval +4

A Robust ADMM-Based Optimization Algorithm For Underwater Acoustic Channel Estimation

no code implementations23 Aug 2023 Tian Tian, Agastya Raj, Bruno Missi Xavier, Ying Zhang, Feiyun Wu, Kunde Yang

Accurate estimation of the Underwater acoustic (UWA) is a key part of underwater communications, especially for coherent systems.

Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching

no code implementations5 Aug 2023 Xinping Zhao, Ying Zhang, Qiang Xiao, Yuming Ren, Yingchun Yang

In short, given a cold-start song request, we expect to retrieve songs with similar audiences and then fastly push the cold-start song to the audiences of the retrieved songs to warm up it.

Contrastive Learning Representation Learning

Bias Behind the Wheel: Fairness Testing of Autonomous Driving Systems

2 code implementations5 Aug 2023 Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Ying Zhang, Xuanzhe Liu

This paper conducts fairness testing of automated pedestrian detection, a crucial but under-explored issue in autonomous driving systems.

Autonomous Driving Fairness +1

Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions

1 code implementation IEEE Transactions on Knowledge and Data Engineering 2023 PDF Han Chen, Hanchen Wang, Hongmei Chen, Ying Zhang, Wenjie Zhang, Xuemin Lin

The interactions between structured entities play important roles in a wide range of applications such as chemistry, material science, biology, and medical science.

Denoising

Where Did the President Visit Last Week? Detecting Celebrity Trips from News Articles

1 code implementation17 Jul 2023 Kai Peng, Ying Zhang, Shuai Ling, Zhaoru Ke, Haipeng Zhang

Although news articles contain travel information of celebrities, it is not possible to perform large-scale and network-wise analysis due to the lack of automatic itinerary detection tools.

Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs

no code implementations17 Jun 2023 Yuhan Wu, Yuanyuan Xu, Wenjie Zhang, Xiwei Xu, Ying Zhang

Research along this line suggests that using multi-modal distribution to represent answer entities is more suitable than uni-modal distribution, as a single query may contain multiple disjoint answer subsets due to the compositional nature of multi-hop queries and the varying latent semantics of relations.

Knowledge Graphs

AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis

1 code implementation31 May 2023 Ru Zhou, Wenya Guo, Xumeng Liu, Shenglong Yu, Ying Zhang, Xiaojie Yuan

Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments.

Aspect-Based Sentiment Analysis Sentence +1

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

2 code implementations23 May 2023 Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, Kailong Wang, Yang Liu

Our study investigates three key research questions: (1) the number of different prompt types that can jailbreak LLMs, (2) the effectiveness of jailbreak prompts in circumventing LLM constraints, and (3) the resilience of ChatGPT against these jailbreak prompts.

Prompt Engineering

Bidirectional Transformer Reranker for Grammatical Error Correction

1 code implementation22 May 2023 Ying Zhang, Hidetaka Kamigaito, Manabu Okumura

Pre-trained seq2seq models have achieved state-of-the-art results in the grammatical error correction task.

Decoder Grammatical Error Correction +4

From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment

1 code implementation19 May 2023 Yu Zhao, Yike Wu, Xiangrui Cai, Ying Zhang, Haiwei Zhang, Xiaojie Yuan

Our approach captures the unified correlation pattern of two kinds of information between entities, and explicitly models the fine-grained interaction between original entity information.

Attribute Entity Alignment +4

A Mountain-Shaped Single-Stage Network for Accurate Image Restoration

1 code implementation9 May 2023 Hu Gao, Jing Yang, Ying Zhang, Ning Wang, Jingfan Yang, Depeng Dang

Image restoration is the task of aiming to obtain a high-quality image from a corrupt input image, such as deblurring and deraining.

Deblurring Decoder +3

Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction

2 code implementations9 May 2023 Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang

The price movement prediction of stock market has been a classical yet challenging problem, with the attention of both economists and computer scientists.

Graph Attention Graph Neural Network +3

Limits of Predictability in Top-N Recommendation

no code implementations23 Mar 2023 En Xu, Zhiwen Yu, Ying Zhang, Bin Guo, Lina Yao

This work investigates such predictability by studying the degree of regularity from a specific set of user behavior data.

Plug-and-Play Regulators for Image-Text Matching

1 code implementation23 Mar 2023 Haiwen Diao, Ying Zhang, Wei Liu, Xiang Ruan, Huchuan Lu

Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching.

Image Retrieval Image-text matching +1

SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements

no code implementations9 Feb 2023 Ying Zhang, Zhiqiang Zhao, Zhuo Feng

This work introduces a highly-scalable spectral graph densification framework (SGL) for learning resistor networks with linear measurements, such as node voltages and currents.

Graph Learning

Disco Intelligent Reflecting Surfaces: Active Channel Aging for Fully-Passive Jamming Attacks

no code implementations1 Feb 2023 Huan Huang, Ying Zhang, Hongliang Zhang, Yi Cai, A. Lee Swindlehurst, Zhu Han

A theoretical analysis of the proposed DIRS-based FPJ that provides an evaluation of the DIRS-based jamming attacks is derived.

Quantization

Audio2Gestures: Generating Diverse Gestures from Audio

no code implementations17 Jan 2023 Jing Li, Di Kang, Wenjie Pei, Xuefei Zhe, Ying Zhang, Linchao Bao, Zhenyu He

Finally, we demonstrate that our method can be readily used to generate motion sequences with user-specified motion clips on the timeline.

Gesture Generation

BadPrompt: Backdoor Attacks on Continuous Prompts

1 code implementation27 Nov 2022 Xiangrui Cai, Haidong Xu, Sihan Xu, Ying Zhang, Xiaojie Yuan

To address this challenge, we propose BadPrompt, a lightweight and task-adaptive algorithm, to backdoor attack continuous prompts.

Backdoor Attack

Joint Secure Communication and Radar Beamforming: A Secrecy-Estimation Rate-Based Design

no code implementations23 Nov 2022 Rong Wen, Ying Zhang, Qiang Li, Youxi Tang

For the AN-aided SRM, by leveraging alternating optimization similar closed-form solution is obtained for the beamformer and the AN covariance matrix.

Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient

1 code implementation24 Oct 2022 Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang

We introduce a new Langevin dynamics based algorithm, called e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear in real-world applications such as quantile estimation, vector quantization, CVaR minimization, and regularized optimization problems involving ReLU neural networks.

Portfolio Optimization Quantization +2

MoSE: Modality Split and Ensemble for Multimodal Knowledge Graph Completion

1 code implementation17 Oct 2022 Yu Zhao, Xiangrui Cai, Yike Wu, Haiwei Zhang, Ying Zhang, Guoqing Zhao, Ning Jiang

Based on these embeddings, in the inference phase, we first make modality-split predictions and then exploit various ensemble methods to combine the predictions with different weights, which models the modality importance dynamically.

Knowledge Graph Completion Relation +1

Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances

1 code implementation COLING 2022 Yike Wu, Yu Zhao, Shiwan Zhao, Ying Zhang, Xiaojie Yuan, Guoqing Zhao, Ning Jiang

In this work, we define the training instances with the same question type but different answers as \textit{superficially similar instances}, and attribute the language priors to the confusion of VQA model on such instances.

Attribute Question Answering +1

Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot Filling

1 code implementation9 Sep 2022 Baohang Zhou, Ying Zhang, Xuhui Sui, Kehui Song, Xiaojie Yuan

To capture the semantic dependency between the syntactic information and task labels, we combine the task specific features with corresponding label embeddings by attention mechanism.

Graph Attention Intent Detection +5

Towards Higher-order Topological Consistency for Unsupervised Network Alignment

no code implementations26 Aug 2022 Qingqiang Sun, Xuemin Lin, Ying Zhang, Wenjie Zhang, Chaoqi Chen

Network alignment task, which aims to identify corresponding nodes in different networks, is of great significance for many subsequent applications.

Semi-supervised segmentation of tooth from 3D Scanned Dental Arches

1 code implementation10 Aug 2022 Ammar Alsheghri, Farnoosh Ghadiri, Ying Zhang, Olivier Lessard, Julia Keren, Farida Cheriet, Francois Guibault

In the dental field, the variability of input data is high and there are no publicly available 3D dental arch datasets.

Clustering

Multi-scale Attentive Image De-raining Networks via Neural Architecture Search

1 code implementation2 Jul 2022 Lei Cai, Yuli Fu, Wanliang Huo, Youjun Xiang, Tao Zhu, Ying Zhang, Huanqiang Zeng, Delu Zeng

The proposed method formulates a new multi-scale attention search space with multiple flexible modules that are favorite to the image de-raining task.

Neural Architecture Search Rain Removal

Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review

no code implementations2 Jul 2022 Hao Wang, Bin Guo, Yating Zeng, Yasan Ding, Chen Qiu, Ying Zhang, Lina Yao, Zhiwen Yu

The intelligent dialogue system, aiming at communicating with humans harmoniously with natural language, is brilliant for promoting the advancement of human-machine interaction in the era of artificial intelligence.

Traffic Context Aware Data Augmentation for Rare Object Detection in Autonomous Driving

no code implementations1 May 2022 Naifan Li, Fan Song, Ying Zhang, Pengpeng Liang, Erkang Cheng

In this work, we propose a systematic study on simple Copy-Paste data augmentation for rare object detection in autonomous driving.

4k Autonomous Driving +4

Probabilistic Models for Manufacturing Lead Times

no code implementations28 Apr 2022 Recep Yusuf Bekci, Yacine Mahdid, Jinling Xing, Nikita Letov, Ying Zhang, Zahid Pasha

In this study, we utilize Gaussian processes, probabilistic neural network, natural gradient boosting, and quantile regression augmented gradient boosting to model lead times of laser manufacturing processes.

Gaussian Processes quantile regression

Influence of the vessel wall geometry on the wall-induced migration of red blood cells

1 code implementation23 Mar 2022 Ying Zhang, Thomas G. Fai

The geometry of the blood vessel wall plays a regulatory role on the motion of red blood cells (RBCs).

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

no code implementations2 Feb 2022 Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu

GatorTron models scale up the clinical language model from 110 million to 8. 9 billion parameters and improve 5 clinical NLP tasks (e. g., 9. 6% and 9. 5% improvement in accuracy for NLI and MQA), which can be applied to medical AI systems to improve healthcare delivery.

Clinical Concept Extraction Language Modeling +7

Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching

no code implementations25 Jan 2022 Hanchen Wang, Ying Zhang, Lu Qin, Wei Wang, Wenjie Zhang, Xuemin Lin

In recent years, many advanced techniques for query vertex ordering (i. e., matching order generation) have been proposed to reduce the unpromising intermediate results according to the preset heuristic rules.

reinforcement-learning Reinforcement Learning +1

Detailed Balance for Particle Models of Reversible Reactions in Bounded Domains

no code implementations11 Jan 2022 Ying Zhang, Samuel A. Isaacson

In bounded domains with no-flux boundary conditions, when choosing unbinding kernels consistent with several commonly used binding kernels, we show that preserving detailed balance of spatial reaction-fluxes at all points requires spatially varying unbinding rate functions near the domain boundary.

Distribution Consistent Neural Architecture Search

no code implementations CVPR 2022 Junyi Pan, Chong Sun, Yizhou Zhou, Ying Zhang, Chen Li

We first theoretically investigate how the weight coupling problem affects the network searching performance from a parameter distribution perspective, and then propose a novel supernet training strategy with a Distribution Consistent Constraint that can provide a good measurement for the extent to which two architectures can share weights.

Neural Architecture Search

Building an AI-ready RSE Workforce

no code implementations9 Nov 2021 Ying Zhang, Matthew A. Gitzendanner, Dan S. Maxwell, Justin W. Richardson, Kaleb E. Smith, Eric A. Stubbs, Brian J. Stucky, Jingchao Zhang, Erik Deumens

Artificial Intelligence has been transforming industries and academic research across the globe, and research software development is no exception.

Decentralized Coordinated State Estimation in Integrated Transmission and Distribution Systems

no code implementations8 Nov 2021 Ying Zhang, Yanbo Chen, Jianhui Wang, Yue Meng, Tianqiao Zhao

Current transmission and distribution system states are mostly unobservable to each other, and state estimation is separately conducted in the two systems owing to the differences in network structures and analytical models.

Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders

no code implementations ICCV 2021 Jing Li, Di Kang, Wenjie Pei, Xuefei Zhe, Ying Zhang, Zhenyu He, Linchao Bao

In order to overcome this problem, we propose a novel conditional variational autoencoder (VAE) that explicitly models one-to-many audio-to-motion mapping by splitting the cross-modal latent code into shared code and motion-specific code.

Gesture Generation