Search Results for author: Yun Li

Found 71 papers, 26 papers with code

HIT: Nested Named Entity Recognition via Head-Tail Pair and Token Interaction

no code implementations EMNLP 2020 Yu Wang, Yun Li, Hanghang Tong, Ziye Zhu

Specifically, we design (1) Head-Tail Detector based on the multi-head self-attention mechanism and bi-affine classifier to detect boundary tokens, and (2) Token Interaction Tagger based on traditional sequence labeling approaches to characterize the internal token connection within the boundary.

named-entity-recognition Named Entity Recognition +2

RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models

1 code implementation6 Jul 2024 Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao

Second, in cases where the model originally responds correctly, applying RAG can lead to an over-reliance on retrieved contexts, resulting in incorrect answers.

Medical Diagnosis RAG +2

Research, Applications and Prospects of Event-Based Pedestrian Detection: A Survey

no code implementations5 Jul 2024 Han Wang, Yuman Nie, Yun Li, Hongjie Liu, Min Liu, Wen Cheng, Yaoxiong Wang

Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range.

Autonomous Driving Pedestrian Detection

PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph

1 code implementation30 Jun 2024 Dazhou Yu, Yuntong Hu, Yun Li, Liang Zhao

Finally, we introduce Multipolygon-GNN, a novel model tailored to leverage the spatial and semantic heterogeneity inherent in the visibility graph.

Computational Efficiency Geographic Question Answering +2

Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction

1 code implementation30 Jun 2024 Dazhou Yu, Xiaoyun Gong, Yun Li, Meikang Qiu, Liang Zhao

Existing models in this area often fall short due to their domain-specific nature and lack a strategy for integrating information from various sources in the absence of ground truth labels.

Graph Neural Network

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

1 code implementation10 Jun 2024 Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, ZongYuan Ge, Gang Li, James Zou, Huaxiu Yao

Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the future of automated and personalized healthcare.


STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics

1 code implementation10 Jun 2024 Jiawen Chen, Muqing Zhou, Wenrong Wu, Jinwei Zhang, Yun Li, Didong Li

Recent advances in multi-modal algorithms have driven and been driven by the increasing availability of large image-text datasets, leading to significant strides in various fields, including computational pathology.

Calibrated Self-Rewarding Vision Language Models

1 code implementation23 May 2024 Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao

In the reward modeling, we employ a step-wise strategy and incorporate visual constraints into the self-rewarding process to place greater emphasis on visual input.

Hallucination Language Modelling +1

Prompt-tuning for Clickbait Detection via Text Summarization

no code implementations17 Apr 2024 Haoxiang Deng, Yi Zhu, Ye Wang, Jipeng Qiang, Yunhao Yuan, Yun Li, Runmei Zhang

To address this problem, we propose a prompt-tuning method for clickbait detection via text summarization in this paper, text summarization is introduced to summarize the contents, and clickbait detection is performed based on the similarity between the generated summary and the contents.

Clickbait Detection Semantic Similarity +2

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

no code implementations30 Mar 2024 Yuji Cao, Huan Zhao, Yuheng Cheng, Ting Shu, Guolong Liu, Gaoqi Liang, Junhua Zhao, Yun Li

With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects such as multi-task learning, sample efficiency, and task planning.

Language Modelling Large Language Model +2

Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning

no code implementations CVPR 2024 Yun Li, Zhe Liu, Hang Chen, Lina Yao

Our framework evaluates the specificity of attributes by considering the diversity of objects they apply to and their related context.

Attribute Compositional Zero-Shot Learning +2

Model Predictive Control Design for Unlocking the Energy Flexibility of Heat Pump and Thermal Energy Storage Systems

no code implementations19 Feb 2024 Weihong Tang, Yun Li, Shalika Walker, Tamas Keviczky

Firstly, for flexibility assessment, a tailored MPC formulation, supplemented by a set of auxiliary linear constraints, is developed to quantitatively assess the flexibility potential inherent in HPTES systems.

Management Model Predictive Control

Multimodal Clinical Trial Outcome Prediction with Large Language Models

1 code implementation9 Feb 2024 Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Yun Li, Hongtu Zhu, Tianfan Fu, Huaxiu Yao

To address these issues, we propose a multimodal mixture-of-experts (LIFTED) approach for clinical trial outcome prediction.

FADI-AEC: Fast Score Based Diffusion Model Guided by Far-end Signal for Acoustic Echo Cancellation

no code implementations8 Jan 2024 Yang Liu, Li Wan, Yun Li, Yiteng Huang, Ming Sun, James Luan, Yangyang Shi, Xin Lei

Despite the potential of diffusion models in speech enhancement, their deployment in Acoustic Echo Cancellation (AEC) has been restricted.

Acoustic echo cancellation Speech Enhancement

Robust Optimal Control With Binary Adjustable Uncertainties

no code implementations18 Dec 2023 Yun Li, Neil Yorke-Smith, Tamas Keviczky

Robust Optimal Control (ROC) with adjustable uncertainties has proven to be effective in addressing critical challenges within modern energy networks, especially the reserve and provision problem.

Unlocking Energy Flexibility From Thermal Inertia of Buildings: A Robust Optimization Approach

no code implementations8 Dec 2023 Yun Li, Neil Yorke-Smith, Tamas Keviczky

In a first step, a robust optimization model is formulated for assessing the energy flexibility of buildings in the presence of uncertain predictions of external conditions, such as ambient temperature, solar irradiation, etc.


Rethinking Samples Selection for Contrastive Learning: Mining of Potential Samples

no code implementations1 Nov 2023 Hengkui Dong, Xianzhong Long, Yun Li

Contrastive learning predicts whether two images belong to the same category by training a model to make their feature representations as close or as far away as possible.

Contrastive Learning Data Augmentation

MNN: Mixed Nearest-Neighbors for Self-Supervised Learning

1 code implementation1 Nov 2023 Xianzhong Long, Chen Peng, Yun Li

In contrastive self-supervised learning, positive samples are typically drawn from the same image but in different augmented views, resulting in a relatively limited source of positive samples.

Self-Supervised Learning

E-Sparse: Boosting the Large Language Model Inference through Entropy-based N:M Sparsity

no code implementations24 Oct 2023 Yun Li, Lin Niu, Xipeng Zhang, Kai Liu, Jianchen Zhu, Zhanhui Kang

Traditional pruning methods are known to be challenging to work in Large Language Models (LLMs) for Generative AI because of their unaffordable training process and large computational demands.

Language Modelling Large Language Model

Multilingual Lexical Simplification via Paraphrase Generation

1 code implementation28 Jul 2023 Kang Liu, Jipeng Qiang, Yun Li, Yunhao Yuan, Yi Zhu, Kaixun Hua

After feeding the input sentence into the encoder of paraphrase modeling, we generate the substitutes based on a novel decoding strategy that concentrates solely on the lexical variations of the complex word.

Diversity Lexical Simplification +4

Multi-network Contrastive Learning Based on Global and Local Representations

no code implementations28 Jun 2023 Weiquan Li, Xianzhong Long, Yun Li

We introduce global and local feature information for self-supervised contrastive learning through multiple networks.

Contrastive Learning Linear evaluation +1

Clickbait Detection via Large Language Models

1 code implementation16 Jun 2023 Han Wang, Yi Zhu, Ye Wang, Yun Li, Yunhao Yuan, Jipeng Qiang

Clickbait, which aims to induce users with some surprising and even thrilling headlines for increasing click-through rates, permeates almost all online content publishers, such as news portals and social media.

Clickbait Detection

Graph Neural Network for spatiotemporal data: methods and applications

no code implementations30 May 2023 Yun Li, Dazhou Yu, Zhenke Liu, Minxing Zhang, Xiaoyun Gong, Liang Zhao

Graph neural networks (GNNs) have emerged as a powerful tool for modeling and understanding data with dependencies to each other such as spatial and temporal dependencies.

Graph Neural Network Weather Forecasting

ParaLS: Lexical Substitution via Pretrained Paraphraser

1 code implementation14 May 2023 Jipeng Qiang, Kang Liu, Yun Li, Yunhao Yuan, Yi Zhu

Lexical substitution (LS) aims at finding appropriate substitutes for a target word in a sentence.


MSVQ: Self-Supervised Learning with Multiple Sample Views and Queues

1 code implementation9 May 2023 Chen Peng, Xianzhong Long, Yun Li

Self-supervised methods based on contrastive learning have achieved great success in unsupervised visual representation learning.

Contrastive Learning Representation Learning +1

Synthetic Hard Negative Samples for Contrastive Learning

no code implementations6 Apr 2023 Hengkui Dong, Xianzhong Long, Yun Li, Lei Chen

Contrastive learning has emerged as an essential approach for self-supervised learning in visual representation learning.

Contrastive Learning Representation Learning +1

Scalable Attribution of Adversarial Attacks via Multi-Task Learning

no code implementations25 Feb 2023 Zhongyi Guo, Keji Han, Yao Ge, Wei Ji, Yun Li

In this paper, AAP is defined as the recognition of three signatures, i. e., {\em attack algorithm}, {\em victim model} and {\em hyperparameter}.

Multi-Task Learning

Sentence Simplification via Large Language Models

2 code implementations23 Feb 2023 Yutao Feng, Jipeng Qiang, Yun Li, Yunhao Yuan, Yi Zhu

Sentence Simplification aims to rephrase complex sentences into simpler sentences while retaining original meaning.

Few-Shot Learning Sentence

PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks

1 code implementation22 Feb 2023 Deqiang Li, Shicheng Cui, Yun Li, Jia Xu, Fu Xiao, Shouhuai Xu

To promote defense effectiveness, we propose a new mixture of attacks to instantiate PAD to enhance deep neural network-based measurements and malware detectors.

Malware Detection

Advancing Example Exploitation Can Alleviate Critical Challenges in Adversarial Training

1 code implementation ICCV 2023 Yao Ge, Yun Li, Keji Han, Junyi Zhu, Xianzhong Long

However, they are susceptible to adversarial examples, which are generated by adding adversarial perturbations to original data.

Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning

no code implementations5 Nov 2022 Zhe Liu, Yun Li, Lina Yao, Xiaojun Chang, Wei Fang, XiaoJun Wu, Yi Yang

We design Semantic Attention (SA) and generative Knowledge Disentanglement (KD) to learn the dependence of feasibility and contextuality, respectively.

Compositional Zero-Shot Learning Disentanglement

SCA: Streaming Cross-attention Alignment for Echo Cancellation

no code implementations1 Nov 2022 Yang Liu, Yangyang Shi, Yun Li, Kaustubh Kalgaonkar, Sriram Srinivasan, Xin Lei

End-to-End deep learning has shown promising results for speech enhancement tasks, such as noise suppression, dereverberation, and speech separation.

Speech Enhancement Speech Separation

Deep Spatial Domain Generalization

1 code implementation3 Oct 2022 Dazhou Yu, Guangji Bai, Yun Li, Liang Zhao

Spatial domain generalization is a spatial extension of domain generalization, which can generalize to unseen spatial domains in continuous 2D space.

Domain Generalization Graph Neural Network +1

Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

no code implementations2 Aug 2022 Liu Yang, Yun Li, Simon X. Yang, Yinzhi Lu, Tan Guo, Keping Yu

Next, the integration of AI and trust management is developed to optimize the intelligence and security.


Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus

no code implementations3 May 2022 Yun Li, Zhe Liu, Lina Yao, Molly Lucas, Jessica J. M. Monaghan, Yu Zhang

With the development of digital technology, machine learning has paved the way for the next generation of tinnitus diagnoses.

BIG-bench Machine Learning EEG +1

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

no code implementations3 May 2022 Yun Li, Zhe Liu, Lina Yao, Jessica J. M. Monaghan, David Mcalpine

The side-aware unsupervised domain adaptation module adapts the class-irrelevant information as domain variance to a new dataset and excludes the variance to obtain the class-distill features for the new dataset classification.

EEG Unsupervised Domain Adaptation

Chinese Idiom Paraphrasing

1 code implementation15 Apr 2022 Jipeng Qiang, Yang Li, Chaowei Zhang, Yun Li, Yunhao Yuan, Yi Zhu, Xindong Wu

Idioms, are a kind of idiomatic expression in Chinese, most of which consist of four Chinese characters.

Machine Translation Paraphrase Generation +1

Prompt-Learning for Short Text Classification

no code implementations23 Feb 2022 Yi Zhu, Xinke Zhou, Jipeng Qiang, Yun Li, Yunhao Yuan, Xindong Wu

In the short text, the extremely short length, feature sparsity, and high ambiguity pose huge challenges to classification tasks.

text-classification Text Classification

Diversity-boosted Generalization-Specialization Balancing for Zero-shot Learning

no code implementations6 Jan 2022 Yun Li, Zhe Liu, Xiaojun Chang, Julian McAuley, Lina Yao

We further propose a differentiable dataset-level balance and update the weights in a linear annealing schedule to simulate network pruning and thus obtain the optimal structure for BSNet with dataset-level balance achieved.

Diversity Meta-Learning +2

Deep Learning-based Predictive Control of Battery Management for Frequency Regulation

1 code implementation4 Jan 2022 Yun Li, Yixiu Wang, Yifu Chen, Kaixun Hua, Jiayang Ren, Ghazaleh Mozafari, Qiugang Lu, Yankai Cao

The design procedure of the proposed scheme consists of two sequential processes: (1) the SL process, in which we first run a simulation with an MPC embedding a low-fidelity battery model to generate a training data set, and then, based on the generated data set, we optimize a DNN-approximated policy using SL algorithms; and (2) the RL process, in which we utilize RL algorithms to improve the performance of the DNN-approximated policy by balancing short-term economic incentives and long-term battery degradation.

Management Model Predictive Control +1

Learning Canonical F-Correlation Projection for Compact Multiview Representation

no code implementations CVPR 2022 Yun-Hao Yuan, Jin Li, Yun Li, Jipeng Qiang, Yi Zhu, Xiaobo Shen, Jianping Gou

With this framework as a tool, we propose a correlative covariation projection (CCP) method by using an explicit nonlinear mapping.

Representation Learning

Boosting Mobile CNN Inference through Semantic Memory

no code implementations5 Dec 2021 Yun Li, Chen Zhang, Shihao Han, Li Lyna Zhang, Baoqun Yin, Yunxin Liu, Mengwei Xu

Human brains are known to be capable of speeding up visual recognition of repeatedly presented objects through faster memory encoding and accessing procedures on activated neurons.

Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning

no code implementations1 Dec 2021 Zhe Liu, Yun Li, Lina Yao, Julian McAuley, Sam Dixon

Our framework outperforms state-of-the-art algorithms on four benchmark datasets in both zero-shot and generalized zero-shot settings, which demonstrates the effectiveness of spiral learning in learning generalizable and complex correlations.

Attribute Zero-Shot Learning

An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning

no code implementations3 Nov 2021 Yun Li, Zhe Liu, Lina Yao, Xianzhi Wang, Julian McAuley, Xiaojun Chang

Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations.

Generalized Zero-Shot Learning

Time-Domain Doppler Biomotion Detections Immune to Unavoidable DC Offsets

no code implementations29 Jun 2021 Qinyi Lv, Lingtong Min, Congqi Cao, Shigang Zhou, Deyun Zhou, Chengkai Zhu, Yun Li, Zhongbo Zhu, Xiaojun Li, Lixin Ran

In the past decades, continuous Doppler radar sensor-based bio-signal detections have attracted many research interests.

DeepCompress: Efficient Point Cloud Geometry Compression

no code implementations2 Jun 2021 Ryan Killea, Yun Li, Saeed Bastani, Paul McLachlan

We propose a more efficient deep learning-based encoder architecture for point clouds compression that incorporates principles from established 3D object detection and image compression architectures.

3D Object Detection Autonomous Driving +3

Attribute-Modulated Generative Meta Learning for Zero-Shot Classification

no code implementations22 Apr 2021 Yun Li, Zhe Liu, Lina Yao, Xiaojun Chang

The promising strategies for ZSL are to synthesize visual features of unseen classes conditioned on semantic side information and to incorporate meta-learning to eliminate the model's inherent bias towards seen classes.

Attribute Classification +6

Task Aligned Generative Meta-learning for Zero-shot Learning

no code implementations3 Mar 2021 Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Guodong Long

Zero-shot learning (ZSL) refers to the problem of learning to classify instances from the novel classes (unseen) that are absent in the training set (seen).

Attribute Generalized Zero-Shot Learning +1

[Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency?

1 code implementation RC 2020 Frank Verhoef, Pieter Bouwman, Yun Li, Rogier van der Weerd

We follow four investigative routes: (i) Replication: we rerun experiments on datasets from the paper in order to replicate the results, and add the results that are missing in the paper; (ii) Code review: we scrutinize the code to validate its correctness; (iii) Evaluation methodology: we extend the set of evaluation metrics used in the paper with the LIME method, in an attempt to resolve inconclusive results; (iv) Generalization to other architectures: we test whether the authorsʼ claims apply to variations of the base model (more complex forms of attention and a BiLSTM encoder).

Diversity Navigate

Chinese Lexical Simplification

1 code implementation14 Oct 2020 Jipeng Qiang, Xinyu Lu, Yun Li, Yunhao Yuan, Yang Shi, Xindong Wu

Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words in a given sentence with simpler alternatives of equivalent meaning.

Language Modelling Lexical Simplification +1

Learning Task-aware Robust Deep Learning Systems

no code implementations11 Oct 2020 Keji Han, Yun Li, Xianzhong Long, Yao Ge

Many works demonstrate that deep learning system is vulnerable to adversarial attack.

Adversarial Attack General Classification

Weight-dependent Gates for Network Pruning

no code implementations4 Jul 2020 Yun Li, Zechun Liu, Weiqun Wu, Haotian Yao, Xiangyu Zhang, Chi Zhang, Baoqun Yin

In this paper, a simple yet effective network pruning framework is proposed to simultaneously address the problems of pruning indicator, pruning ratio, and efficiency constraint.

Network Pruning

LSBert: A Simple Framework for Lexical Simplification

1 code implementation25 Jun 2020 Jipeng Qiang, Yun Li, Yi Zhu, Yunhao Yuan, Xindong Wu

Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning, to simplify the sentence.

Language Modelling Lexical Simplification +2

Agglomerative Neural Networks for Multi-view Clustering

no code implementations12 May 2020 Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Feiping Nie

Conventional multi-view clustering methods seek for a view consensus through minimizing the pairwise discrepancy between the consensus and subviews.


Lexical Simplification with Pretrained Encoders

3 code implementations14 Jul 2019 Jipeng Qiang, Yun Li, Yi Zhu, Yunhao Yuan, Xindong Wu

Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning.

Language Modelling Lexical Simplification +1

A simple and effective postprocessing method for image classification

no code implementations19 Jun 2019 Yan Liu, Yun Li, Yunhao Yuan, Jipeng Qiang

Whether it is computer vision, natural language processing or speech recognition, the essence of these applications is to obtain powerful feature representations that make downstream applications completion more efficient.

Classification General Classification +3

STTM: A Tool for Short Text Topic Modeling

1 code implementation7 Aug 2018 Jipeng Qiang, Yun Li, Yunhao Yuan, Wei Liu, Xindong Wu

Along with the emergence and popularity of social communications on the Internet, topic discovery from short texts becomes fundamental to many applications that require semantic understanding of textual content.

Information Retrieval

Controlled Tracking in Urban Terrain: Closing the Loop

no code implementations1 May 2018 Patricia R. Barbosa, Yugandhar Sarkale, Edwin K. P. Chong, Yun Li, Sofia Suvorova, Bill Moran

We investigate the challenging problem of integrating detection, signal processing, target tracking, and adaptive waveform scheduling with lookahead in urban terrain.

Signal Processing Systems and Control

Simplex Search Based Brain Storm Optimization

no code implementations24 Oct 2017 Wei Chen, YingYing Cao, Shi Cheng, Yifei Sun, Qunfeng Liu, Yun Li

Through modeling human's brainstorming process, the brain storm optimization (BSO) algorithm has become a promising population-based evolutionary algorithm.

Constraints on Primordial Magnetic Fields from Planck combined with the South Pole Telescope CMB B-mode polarization measurements

3 code implementations2 Nov 2016 Alex Zucca, Yun Li, Levon Pogosian

We use the publicly released SPT B-mode polarization spectrum, along with the temperature and polarization data from the Planck satellite, to derive constraints on the magnitude, the spectral index and the energy scale at which the PMF was generated.

Cosmology and Nongalactic Astrophysics

Video Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models

no code implementations9 Mar 2015 Aswin C. Sankaranarayanan, Lina Xu, Christoph Studer, Yun Li, Kevin Kelly, Richard G. Baraniuk

In this paper, we propose the CS multi-scale video (CS-MUVI) sensing and recovery framework for high-quality video acquisition and recovery using SMCs.

Compressive Sensing Optical Flow Estimation +1

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