Search Results for author: Han Li

Found 64 papers, 19 papers with code

Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysis

no code implementations25 Feb 2024 Zihan Liu, Han Li, Anfan Chen, Renwen Zhang, Yi-chieh Lee

We find Chinese participants tended to view CAs hedonically, perceived voice-based and physically embodied CAs as warmer and more competent, and generally expressed positive emotions.

LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition

no code implementations15 Feb 2024 Jinyuan Li, Han Li, Di Sun, Jiahao Wang, Wenkun Zhang, Zan Wang, Gang Pan

Grounded Multimodal Named Entity Recognition (GMNER) is a nascent multimodal task that aims to identify named entities, entity types and their corresponding visual regions.

named-entity-recognition Named Entity Recognition +6

Optimal dynamic climate adaptation pathways: a case study of New York City

no code implementations5 Feb 2024 Chi Truong, Matteo Malavasi, Han Li, Stefan Trueck, Pavel V. Shevchenko

We model the severity of extreme sea level events using the block maxima approach from extreme value theory, and then develop a real options framework, factoring in climate change, sea level rise uncertainty, and the growth in asset exposure.

RIDERS: Radar-Infrared Depth Estimation for Robust Sensing

1 code implementation3 Feb 2024 Han Li, Yukai Ma, Yuehao Huang, Yaqing Gu, Weihua Xu, Yong liu, Xingxing Zuo

Dense depth recovery is crucial in autonomous driving, serving as a foundational element for obstacle avoidance, 3D object detection, and local path planning.

3D Object Detection Autonomous Driving +3

Future Impact Decomposition in Request-level Recommendations

no code implementations29 Jan 2024 Xiaobei Wang, Shuchang Liu, Xueliang Wang, Qingpeng Cai, Lantao Hu, Han Li, Peng Jiang, Kun Gai, Guangming Xie

Furthermore, we show that a reward-based future decomposition strategy can better express the item-wise future impact and improve the recommendation accuracy in the long term.

Recommendation Systems

PepGB: Facilitating peptide drug discovery via graph neural networks

no code implementations26 Jan 2024 Yipin Lei, Xu Wang, Meng Fang, Han Li, Xiang Li, Jianyang Zeng

In summary, our proposed frameworks can serve as potent tools to facilitate peptide early drug discovery.

Contrastive Learning Drug Discovery

RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scale

no code implementations9 Jan 2024 Han Li, Yukai Ma, Yaqing Gu, Kewei Hu, Yong liu, Xingxing Zuo

We propose a Radar-Camera framework for highly accurate and fine-detailed dense depth estimation with four stages, including monocular depth prediction, global scale alignment of monocular depth with sparse Radar points, quasi-dense scale estimation through learning the association between Radar points and image patches, and local scale refinement of dense depth using a scale map learner.

Depth Estimation Depth Prediction

Towards Efficient and Effective Text-to-Video Retrieval with Coarse-to-Fine Visual Representation Learning

no code implementations1 Jan 2024 Kaibin Tian, Yanhua Cheng, Yi Liu, Xinglin Hou, Quan Chen, Han Li

To address this issue, we adopt multi-granularity visual feature learning, ensuring the model's comprehensiveness in capturing visual content features spanning from abstract to detailed levels during the training phase.

Representation Learning Retrieval +3

LoCo: Locally Constrained Training-Free Layout-to-Image Synthesis

no code implementations21 Nov 2023 Peiang Zhao, Han Li, Ruiyang Jin, S. Kevin Zhou

Recent text-to-image diffusion models have reached an unprecedented level in generating high-quality images.

Image Generation

Frequency-Aware Transformer for Learned Image Compression

no code implementations25 Oct 2023 Han Li, Shaohui Li, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong

Learned image compression (LIC) has gained traction as an effective solution for image storage and transmission in recent years.

Image Compression

Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems

no code implementations16 Oct 2023 Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai

Concretely, we employ multi-task learning to adaptively combine the optimization of relaxed and full targets, which refers to metrics Recall@m@k and OPA respectively.

Learning-To-Rank Multi-Task Learning +1

Interpretable Diffusion via Information Decomposition

1 code implementation12 Oct 2023 Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg

For diffusion models, we show that a natural non-negative decomposition of mutual information emerges, allowing us to quantify informative relationships between words and pixels in an image.

Image Generation Vision-Language Segmentation

Discovering Sounding Objects by Audio Queries for Audio Visual Segmentation

no code implementations18 Sep 2023 Shaofei Huang, Han Li, Yuqing Wang, Hongji Zhu, Jiao Dai, Jizhong Han, Wenge Rong, Si Liu

Explicit object-level semantic correspondence between audio and visual modalities is established by gathering object information from visual features with predefined audio queries.

Object Semantic correspondence

Cross-Domain Product Representation Learning for Rich-Content E-Commerce

1 code implementation ICCV 2023 Xuehan Bai, Yan Li, Yanhua Cheng, Wenjie Yang, Quan Chen, Han Li

It is the first dataset to cover product pages, short videos, and live streams simultaneously, providing the basis for establishing a unified product representation across different media domains.

Representation Learning

Cross-view Semantic Alignment for Livestreaming Product Recognition

1 code implementation ICCV 2023 Wenjie Yang, Yiyi Chen, Yan Li, Yanhua Cheng, Xudong Liu, Quan Chen, Han Li

Moreover, a cRoss-vIew semantiC alignmEnt (RICE) model is proposed to learn discriminative instance features from the image and video views of the products.

Contrastive Learning

ActionPrompt: Action-Guided 3D Human Pose Estimation With Text and Pose Prompting

no code implementations18 Jul 2023 Hongwei Zheng, Han Li, Bowen Shi, Wenrui Dai, Botao Wan, Yu Sun, Min Guo, Hongkai Xiong

Recent 2D-to-3D human pose estimation (HPE) utilizes temporal consistency across sequences to alleviate the depth ambiguity problem but ignore the action related prior knowledge hidden in the pose sequence.

3D Human Pose Estimation

D3L: Decomposition of 3D Rotation and Lift from 2D Joint to 3D for Human Mesh Recovery

no code implementations10 Jun 2023 Xiaoyang Hao, Han Li, Jun Cheng, Lei Wang

However, these methods present rotation semantic ambiguity, rotation error accumulation, and shape estimation overfitting, which also leads to errors in the estimated pose.

Human Mesh Recovery Pose Estimation +1

Multi-Epoch Learning for Deep Click-Through Rate Prediction Models

no code implementations31 May 2023 Zhaocheng Liu, Zhongxiang Fan, Jian Liang, Dongying Kong, Han Li

However, it is still unknown whether a multi-epoch training paradigm could achieve better results, as the best performance is usually achieved by one-epoch training.

Click-Through Rate Prediction Data Augmentation

Prompting ChatGPT in MNER: Enhanced Multimodal Named Entity Recognition with Auxiliary Refined Knowledge

1 code implementation20 May 2023 Jinyuan Li, Han Li, Zhuo Pan, Di Sun, Jiahao Wang, Wenkun Zhang, Gang Pan

However, these methods either neglect the necessity of providing the model with external knowledge, or encounter issues of high redundancy in the retrieved knowledge.

 Ranked #1 on Multi-modal Named Entity Recognition on Twitter-2017 (using extra training data)

Multi-modal Named Entity Recognition named-entity-recognition +1

Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation

no code implementations15 Feb 2023 Han Li, Bowen Shi, Wenrui Dai, Hongwei Zheng, Botao Wang, Yu Sun, Min Guo, Chenlin Li, Junni Zou, Hongkai Xiong

There has been a recent surge of interest in introducing transformers to 3D human pose estimation (HPE) due to their powerful capabilities in modeling long-term dependencies.

3D Human Pose Estimation Position

Mixed-order self-paced curriculum learning for universal lesion detection

no code implementations9 Feb 2023 Han Li, Hu Han, S. Kevin Zhou

Most SCL methods commonly adopt a loss-based strategy of estimating data difficulty and deweighting the `hard' samples in the early training stage.

Lesion Detection

Fairness in Medical Image Analysis and Healthcare: A Literature Survey

no code implementations27 Sep 2022 Zikang Xu, Jun Li, Qingsong Yao, Han Li, S. Kevin Zhou

Machine learning-enabled medical imaging analysis has become a vital part of the automatic diagnosis system.

Fairness object-detection +1

KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction

1 code implementation2 Jun 2022 Han Li, Dan Zhao, Jianyang Zeng

In this paper, we argue that there exist two major issues hindering current self-supervised learning methods from obtaining desired performance on molecular property prediction, that is, the ill-defined pre-training tasks and the limited model capacity.

Graph Representation Learning Molecular Property Prediction +2

SATr: Slice Attention with Transformer for Universal Lesion Detection

no code implementations13 Mar 2022 Han Li, Long Chen, Hu Han, S. Kevin Zhou

Universal Lesion Detection (ULD) in computed tomography plays an essential role in computer-aided diagnosis.

Lesion Detection

DNN Training Acceleration via Exploring GPGPU Friendly Sparsity

no code implementations11 Mar 2022 Zhuoran Song, Yihong Xu, Han Li, Naifeng Jing, Xiaoyao Liang, Li Jiang

The training phases of Deep neural network~(DNN) consumes enormous processing time and energy.

MVP-Net: Multiple View Pointwise Semantic Segmentation of Large-Scale Point Clouds

no code implementations30 Jan 2022 Chuanyu Luo, Xiaohan Li, Nuo Cheng, Han Li, Shengguang Lei, Pu Li

The pipeline of most pointwise point cloud semantic segmentation methods includes points sampling, neighbor searching, feature aggregation, and classification.

Autonomous Driving Segmentation +1

Pareto Domain Adaptation

1 code implementation NeurIPS 2021 Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li, Chi Harold Liu, Han Li, Di Liu, Guoren Wang

Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source.

Domain Adaptation Image Classification +2

Incentive Compatible Pareto Alignment for Multi-Source Large Graphs

1 code implementation6 Dec 2021 Jian Liang, Fangrui Lv, Di Liu, Zehui Dai, Xu Tian, Shuang Li, Fei Wang, Han Li

Challenges of the problem include 1) how to align large-scale entities between sources to share information and 2) how to mitigate negative transfer from joint learning multi-source data.

Hierarchical Graph Networks for 3D Human Pose Estimation

1 code implementation23 Nov 2021 Han Li, Bowen Shi, Wenrui Dai, Yabo Chen, Botao Wang, Yu Sun, Min Guo, Chenlin Li, Junni Zou, Hongkai Xiong

Recent 2D-to-3D human pose estimation works tend to utilize the graph structure formed by the topology of the human skeleton.

3D Human Pose Estimation

Context-aware Tree-based Deep Model for Recommender Systems

no code implementations22 Sep 2021 Daqing Chang, Jintao Liu, Ziru Xu, Han Li, Han Zhu, Xiaoqiang Zhu

Vertically, a parent fusion layer is designed in M to transmit the user preference representation in higher levels of T to the current level, grasping the essence that tree-based methods are generating the candidate set from coarse to detail during the beam search retrieval.

Recommendation Systems Retrieval

Learning Slice-Aware Representations with Mixture of Attentions

no code implementations Findings (ACL) 2021 Cheng Wang, Sungjin Lee, Sunghyun Park, Han Li, Young-Bum Kim, Ruhi Sarikaya

Real-world machine learning systems are achieving remarkable performance in terms of coarse-grained metrics like overall accuracy and F-1 score.

Natural Language Understanding

Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration

no code implementations4 Mar 2021 Han Li, Sunghyun Park, Aswarth Dara, Jinseok Nam, Sungjin Lee, Young-Bum Kim, Spyros Matsoukas, Ruhi Sarikaya

Ensuring model robustness or resilience in the skill routing component is an important problem since skills may dynamically change their subscription in the ontology after the skill routing model has been deployed to production.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Phase Diagram of Triangular Lattice Quantum Ising Model under External Field

no code implementations27 Jan 2021 Yuan Da Liao, Han Li, Zheng Yan, Hao-Tian Wei, Wei Li, Yang Qi, Zi Yang Meng

Quantum Ising model on a triangular lattice hosts a finite temperature Berezinskii-Kosterlitz-Thouless (BKT) phase with emergent U(1) symmetry, and it will transit into an up-up-down (UUD) phase with $C_3$ symmetry breaking upon an infinitesimal external field along the longitudinal direction, but the overall phase diagram spanned by the axes of external field and temperature remains opaque due to the lack of systematic invesitgations with controlled methodologies.

Strongly Correlated Electrons Statistical Mechanics

A scalable framework for learning from implicit user feedback to improve natural language understanding in large-scale conversational AI systems

no code implementations EMNLP 2021 Sunghyun Park, Han Li, Ameen Patel, Sidharth Mudgal, Sungjin Lee, Young-Bum Kim, Spyros Matsoukas, Ruhi Sarikaya

Natural Language Understanding (NLU) is an established component within a conversational AI or digital assistant system, and it is responsible for producing semantic understanding of a user request.

Natural Language Understanding

Learning to Infer User Hidden States for Online Sequential Advertising

no code implementations3 Sep 2020 Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Wei-Nan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai

To drive purchase in online advertising, it is of the advertiser's great interest to optimize the sequential advertising strategy whose performance and interpretability are both important.

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction

no code implementations20 Aug 2020 Liyi Guo, Rui Lu, Haoqi Zhang, Junqi Jin, Zhenzhe Zheng, Fan Wu, Jin Li, Haiyang Xu, Han Li, Wenkai Lu, Jian Xu, Kun Gai

For e-commerce platforms such as Taobao and Amazon, advertisers play an important role in the entire digital ecosystem: their behaviors explicitly influence users' browsing and shopping experience; more importantly, advertiser's expenditure on advertising constitutes a primary source of platform revenue.

Marketing

Bounding Maps for Universal Lesion Detection

no code implementations18 Jul 2020 Han Li, Hu Han, S. Kevin Zhou

The bounding maps (BMs) are used in two-stage anchor-based ULD frameworks to reduce the FP rate.

Lesion Detection Region Proposal

The Statistical Characteristics of Power-Spectrum Subband Energy Ratios under Additive Gaussian White Noise

no code implementations8 Jul 2020 Han Li, Yanzhu Hu, Song Wang, Zhen Meng

When Gaussian white noise was mixed with the known signal, the resulting PSER followed a doubly non-central beta distribution.

valid

Handling Rare Entities for Neural Sequence Labeling

no code implementations ACL 2020 Yangming Li, Han Li, Kaisheng Yao, Xiaolong Li

One great challenge in neural sequence labeling is the data sparsity problem for rare entity words and phrases.

Learning Optimal Tree Models Under Beam Search

1 code implementation ICML 2020 Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai

Retrieving relevant targets from an extremely large target set under computational limits is a common challenge for information retrieval and recommendation systems.

Information Retrieval Recommendation Systems +1

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

no code implementations9 May 2020 Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai

Bipartite b-matching is fundamental in algorithm design, and has been widely applied into economic markets, labor markets, etc.

Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition

1 code implementation16 Sep 2019 Zeju Li, Han Li, Hu Han, Gonglei Shi, Jiannan Wang, S. Kevin Zhou

We hereby propose a decomposition generative adversarial network (DecGAN) to anatomically decompose a CXR image but with unpaired data.

Anatomy Disentanglement +1

Spectral-based Graph Convolutional Network for Directed Graphs

no code implementations21 Jul 2019 Yi Ma, Jianye Hao, Yaodong Yang, Han Li, Junqi Jin, Guangyong Chen

Our approach can work directly on directed graph data in semi-supervised nodes classification tasks.

Detecting Customer Complaint Escalation with Recurrent Neural Networks and Manually-Engineered Features

no code implementations NAACL 2019 Wei Yang, Luchen Tan, Chunwei Lu, Anqi Cui, Han Li, Xi Chen, Kun Xiong, Muzi Wang, Ming Li, Jian Pei, Jimmy Lin

Consumers dissatisfied with the normal dispute resolution process provided by an e-commerce company{'}s customer service agents have the option of escalating their complaints by filing grievances with a government authority.

Learning Adaptive Display Exposure for Real-Time Advertising

no code implementations10 Sep 2018 Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Wei-Nan Zhang, Jun Wang, Xiaotian Hao, Yixi Wang, Han Li, Jian Xu, Kun Gai

In this paper, we investigate the problem of advertising with adaptive exposure: can we dynamically determine the number and positions of ads for each user visit under certain business constraints so that the platform revenue can be increased?

Learning Tree-based Deep Model for Recommender Systems

4 code implementations8 Jan 2018 Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai

In systems with large corpus, however, the calculation cost for the learnt model to predict all user-item preferences is tremendous, which makes full corpus retrieval extremely difficult.

Recommendation Systems Retrieval +1

Toward a System Building Agenda for Data Integration

no code implementations29 Sep 2017 AnHai Doan, Adel Ardalan, Jeffrey R. Ballard, Sanjib Das, Yash Govind, Pradap Konda, Han Li, Erik Paulson, Paul Suganthan G. C., Haojun Zhang

They provide tools to address the "pain points" of the steps, and tools are built on top of the Python data science and Big Data ecosystem (PyData).

Databases

Deep Interest Network for Click-Through Rate Prediction

17 code implementations21 Jun 2017 Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai

In this way, user features are compressed into a fixed-length representation vector, in regardless of what candidate ads are.

Click-Through Rate Prediction

Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction

3 code implementations18 Apr 2017 Kun Gai, Xiaoqiang Zhu, Han Li, Kai Liu, Zhe Wang

CTR prediction in real-world business is a difficult machine learning problem with large scale nonlinear sparse data.

Click-Through Rate Prediction Feature Engineering

Optimized Cost per Click in Taobao Display Advertising

no code implementations27 Feb 2017 Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai

Moreover, the platform has to be responsible for the business revenue and user experience.

Test

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