Search Results for author: Yuchen Li

Found 43 papers, 17 papers with code

When Search Engine Services meet Large Language Models: Visions and Challenges

no code implementations28 Jun 2024 Haoyi Xiong, Jiang Bian, Yuchen Li, Xuhong LI, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal

Combining Large Language Models (LLMs) with search engine services marks a significant shift in the field of services computing, opening up new possibilities to enhance how we search for and retrieve information, understand content, and interact with internet services.

Learning-To-Rank

Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation

no code implementations15 Jun 2024 Qingquan Zhang, Yuchen Li, Yuhang Lin, Handing Wang, Jialin Liu

Designed to bridge theoretical optimisation strategies with practical game generation applications, the interface is also accessible to both researchers and beginners to multi-objective evolutionary algorithms or procedural content generation on a website.

Diversity Evolutionary Algorithms

AutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}

1 code implementation23 May 2024 Bin Lei, Yuchen Li, Qiuwu Chen

We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo (April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test ($\mathbf{90. 9\%}$ vs. $\mathbf{90. 2\%}$).

Class-level Code Generation Code Completion +7

Enabling Roll-up and Drill-down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management

no code implementations8 May 2024 Sha Wang, Yuchen Li, Hanhua Xiao, Zhifeng Bao, Lambert Deng, Yanfei Dong

Efficient news exploration is crucial in real-world applications, particularly within the financial sector, where numerous control and risk assessment tasks rely on the analysis of public news reports.

Knowledge Graphs Management

Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms

no code implementations5 May 2024 Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu

Our focus is on understanding when inexact RGD converges and what is the complexity in the general nonconvex and constrained setting.

Riemannian optimization Tensor Decomposition

Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm

no code implementations1 Apr 2024 Zhonghao Lyu, Yuchen Li, Guangxu Zhu, Jie Xu, H. Vincent Poor, Shuguang Cui

Based on our analytical results, we then propose a joint communication and computation resource management design to minimize an average squared gradient norm bound, subject to constraints on the transmit power, overall system energy consumption, and training delay.

Management

Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective

no code implementations9 Jan 2024 Haoyi Xiong, Xuhong LI, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du

Given the complexity and lack of transparency in deep neural networks (DNNs), extensive efforts have been made to make these systems more interpretable or explain their behaviors in accessible terms.

Data Valuation Decision Making +2

Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization

no code implementations16 Dec 2023 Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu

Block majorization-minimization (BMM) is a simple iterative algorithm for nonconvex optimization that sequentially minimizes a majorizing surrogate of the objective function in each block coordinate while the other block coordinates are held fixed.

Dictionary Learning Riemannian optimization

Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars

no code implementations NeurIPS 2023 Kaiyue Wen, Yuchen Li, Bingbin Liu, Andrej Risteski

Interpretability methods aim to understand the algorithm implemented by a trained model (e. g., a Transofmer) by examining various aspects of the model, such as the weight matrices or the attention patterns.

LEMMA

Web News Timeline Generation with Extended Task Prompting

no code implementations20 Nov 2023 Sha Wang, Yuchen Li, Hanhua Xiao, Lambert Deng, Yanfei Dong

The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time.

Management

3DCoMPaT$^{++}$: An improved Large-scale 3D Vision Dataset for Compositional Recognition

1 code implementation27 Oct 2023 Habib Slim, Xiang Li, Yuchen Li, Mahmoud Ahmed, Mohamed Ayman, Ujjwal Upadhyay, Ahmed Abdelreheem, Arpit Prajapati, Suhail Pothigara, Peter Wonka, Mohamed Elhoseiny

In this work, we present 3DCoMPaT$^{++}$, a multimodal 2D/3D dataset with 160 million rendered views of more than 10 million stylized 3D shapes carefully annotated at the part-instance level, alongside matching RGB point clouds, 3D textured meshes, depth maps, and segmentation masks.

Comparative study of microgrid optimal scheduling under multi-optimization algorithm fusion

no code implementations3 Oct 2023 Hongyi Duan, Qingyang Li, Yuchen Li, Jianan Zhang, Yuming Xie

As global attention on renewable and clean energy grows, the research and implementation of microgrids become paramount.

Scheduling

Improvement and Enhancement of YOLOv5 Small Target Recognition Based on Multi-module Optimization

no code implementations3 Oct 2023 Qingyang Li, Yuchen Li, Hongyi Duan, JiaLiang Kang, Jianan Zhang, Xueqian Gan, Ruotong Xu

In this paper, the limitations of YOLOv5s model on small target detection task are deeply studied and improved.

FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusion

no code implementations14 Aug 2023 Siyu Teng, Luxi Li, Yuchen Li, Xuemin Hu, Lingxi Li, Yunfeng Ai, Long Chen

Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation.

Motion Planning Scheduling +1

Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning

no code implementations3 Jun 2023 Long Chen, Siyu Teng, Bai Li, Xiaoxiang Na, Yuchen Li, Zixuan Li, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their promise for enhanced safety, efficiency, and economic benefits.

Autonomous Driving Ethics

Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

no code implementations12 May 2023 Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions.

Autonomous Driving Ethics

Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

no code implementations30 Mar 2023 Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.

Autonomous Driving Ethics

Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

no code implementations17 Mar 2023 Siyu Teng, Xuemin Hu, Peng Deng, Bai Li, Yuchen Li, Dongsheng Yang, Yunfeng Ai, Lingxi Li, Zhe XuanYuan, Fenghua Zhu, Long Chen

Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value.

Autonomous Driving Motion Planning

How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding

1 code implementation7 Mar 2023 Yuchen Li, Yuanzhi Li, Andrej Risteski

While the successes of transformers across many domains are indisputable, accurate understanding of the learning mechanics is still largely lacking.

CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion

no code implementations13 Dec 2022 Zizhang Wu, Man Wang, Weiwei Sun, Yuchen Li, Tianhao Xu, Fan Wang, Keke Huang

Channel and spatial attention mechanism has proven to provide an evident performance boost of deep convolution neural networks (CNNs).

Image Classification Instance Segmentation +3

Balancing Utility and Fairness in Submodular Maximization (Technical Report)

1 code implementation2 Nov 2022 Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang

Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications -- including data summarization, influence maximization, and recommendation.

Combinatorial Optimization Data Summarization +1

SFF-DA: Sptialtemporal Feature Fusion for Detecting Anxiety Nonintrusively

no code implementations12 Aug 2022 Haimiao Mo, Yuchen Li, Shanlin Yang, Wei zhang, Shuai Ding

To address these issues, we propose a framework with spatiotemporal feature fusion for detecting anxiety nonintrusively.

Contrasting the landscape of contrastive and non-contrastive learning

1 code implementation29 Mar 2022 Ashwini Pokle, Jinjin Tian, Yuchen Li, Andrej Risteski

Some recent works however have shown promising results for non-contrastive learning, which does not require negative samples.

Contrastive Learning

Improving greedy core-set configurations for active learning with uncertainty-scaled distances

no code implementations9 Feb 2022 Yuchen Li, Frank Rudzicz

We scale perceived distances of the core-set algorithm by a factor of uncertainty and search for low-confidence configurations, finding significant improvements in sample efficiency across CIFAR10/100 and SVHN image classification, especially in larger acquisition sizes.

Active Learning Image Classification

AutoMine: An Unmanned Mine Dataset

no code implementations CVPR 2022 Yuchen Li, Zixuan Li, Siyu Teng, Yu Zhang, YuHang Zhou, Yuchang Zhu, Dongpu Cao, Bin Tian, Yunfeng Ai, Zhe XuanYuan, Long Chen

The main contributions of the AutoMine dataset are as follows: 1. The first autonomous driving dataset for perception and localization in mine scenarios.

Autonomous Driving

Privacy Threats Analysis to Secure Federated Learning

no code implementations24 Jun 2021 Yuchen Li, Yifan Bao, Liyao Xiang, Junhan Liu, Cen Chen, Li Wang, Xinbing Wang

Federated learning is emerging as a machine learning technique that trains a model across multiple decentralized parties.

BIG-bench Machine Learning Federated Learning +1

The Limitations of Limited Context for Constituency Parsing

no code implementations ACL 2021 Yuchen Li, Andrej Risteski

Concretely, we ground this question in the sandbox of probabilistic context-free-grammars (PCFGs), and identify a key aspect of the representational power of these approaches: the amount and directionality of context that the predictor has access to when forced to make parsing decision.

Constituency Parsing Language Modelling

Block majorization-minimization with diminishing radius for constrained nonconvex optimization

1 code implementation7 Dec 2020 Hanbaek Lyu, Yuchen Li

Block majorization-minimization (BMM) is a simple iterative algorithm for nonconvex constrained optimization that sequentially minimizes majorizing surrogates of the objective function in each block coordinate while the other coordinates are held fixed.

Tensor Decomposition

Efficient Sampling Algorithms for Approximate Temporal Motif Counting (Extended Version)

1 code implementation28 Jul 2020 Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan

We first propose a generic edge sampling (ES) algorithm for estimating the number of instances of any temporal motif.

GRMR: Generalized Regret-Minimizing Representatives

no code implementations19 Jul 2020 Yanhao Wang, Michael Mathioudakis, Yuchen Li, Kian-Lee Tan

Extracting a small subset of representative tuples from a large database is an important task in multi-criteria decision making.

Data Structures and Algorithms Databases

A Fully Dynamic Algorithm for k-Regret Minimizing Sets

1 code implementation29 May 2020 Yanhao Wang, Yuchen Li, Raymond Chi-Wing Wong, Kian-Lee Tan

Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation.

Databases Data Structures and Algorithms

Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity

1 code implementation4 Sep 2019 Yu Shi, Jiaming Shen, Yuchen Li, Naijing Zhang, Xinwei He, Zhengzhi Lou, Qi Zhu, Matthew Walker, Myunghwan Kim, Jiawei Han

Extensive experiments on two large real-world datasets demonstrate the effectiveness of HyperMine and the utility of modeling context granularity.

Knowledge Graphs

Variations on the Chebyshev-Lagrange Activation Function

2 code implementations24 Jun 2019 Yuchen Li, Frank Rudzicz, Jekaterina Novikova

We seek to improve the data efficiency of neural networks and present novel implementations of parameterized piece-wise polynomial activation functions.

Coresets for Minimum Enclosing Balls over Sliding Windows

1 code implementation9 May 2019 Yanhao Wang, Yuchen Li, Kian-Lee Tan

This paper investigates the problem of maintaining a coreset to preserve the minimum enclosing ball (MEB) for a sliding window of points that are continuously updated in a data stream.

Semi-Supervised Few-Shot Learning with Prototypical Random Walks

1 code implementation6 Mar 2019 Ahmed Ayyad, Yuchen Li, Nassir Navab, Shadi Albarqouni, Mohamed Elhoseiny

We develop a random walk semi-supervised loss that enables the network to learn representations that are compact and well-separated.

Few-Shot Learning

Context-Sensitive Malicious Spelling Error Correction

no code implementations23 Jan 2019 Hongyu Gong, Yuchen Li, Suma Bhat, Pramod Viswanath

Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection.

Spam detection Spelling Correction +1

ChainGAN: A sequential approach to GANs

1 code implementation ICLR 2019 Safwan Hossain, Kiarash Jamali, Yuchen Li, Frank Rudzicz

Current approaches attempt to learn the transformation from a noise sample to a generated data sample in one shot.

Efficient Representative Subset Selection over Sliding Windows

1 code implementation15 Jun 2017 Yanhao Wang, Yuchen Li, Kian-Lee Tan

By keeping much fewer checkpoints, KW$^{+}$ achieves higher efficiency than KW while still guaranteeing a $\frac{1-\varepsilon'}{2+2d}$-approximate solution for SMDK.

Real-Time Influence Maximization on Dynamic Social Streams

no code implementations6 Feb 2017 Yanhao Wang, Qi Fan, Yuchen Li, Kian-Lee Tan

Influence maximization (IM), which selects a set of $k$ users (called seeds) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications such as viral marketing and network monitoring.

Social and Information Networks Data Structures and Algorithms

Cannot find the paper you are looking for? You can Submit a new open access paper.