170 citations · 363 across the 19 of their papers we have counts for
19 papers
PureCC: Pure Learning for Text-to-Image Concept Customization
Zhichao Liao, Xiaole Xian, Qingyu Li +7
Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often neglect the influence on the original…
Disentangled Interest Network for Out-of-Distribution CTR Prediction
Yu Zheng, Chen Gao, Jianxin Chang +5
Click-through rate (CTR) prediction, which estimates the probability of a user clicking on a given item, is a critical task for online information services. Existing approaches oft…
Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
Miaomiao Cai, Min Hou, Lei Chen +4
Collaborative Filtering~(CF) plays a crucial role in modern recommender systems, leveraging historical user-item interactions to provide personalized suggestions. However, CF-based…
Distilling Textual Priors from LLM to Efficient Image Fusion
Ran Zhang, Xuanhua He, Ke Cao +4
Multi-modality image fusion aims to synthesize a single, comprehensive image from multiple source inputs. Traditional approaches, such as CNNs and GANs, offer efficiency but strugg…
Generalist Virtual Agents: A Survey on Autonomous Agents Across Digital Platforms
Minghe Gao, Wendong Bu, Bingchen Miao +7
In this paper, we introduce the Generalist Virtual Agent (GVA), an autonomous entity engineered to function across diverse digital platforms and environments, assisting users by ex…
Enhancing ID-based Recommendation with Large Language Models
Lei Chen, Chen Gao, Xiaoyi Du +4
Large Language Models (LLMs) have recently garnered significant attention in various domains, including recommendation systems. Recent research leverages the capabilities of LLMs t…
PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation
Jinpeng Hu, Tengteng Dong, Luo Gang +6
Mental health has attracted substantial attention in recent years and LLM can be an effective technology for alleviating this problem owing to its capability in text understanding…
Gradually Vanishing Gap in Prototypical Network for Unsupervised Domain Adaptation
Shanshan Wang, Hao Zhou, Xun Yang +4
Unsupervised domain adaptation (UDA) is a critical problem for transfer learning, which aims to transfer the semantic information from labeled source domain to unlabeled target dom…
Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
Zhiyong Cheng, Jianhua Dong, Fan Liu +3
Multi-behavioral recommender systems have emerged as a solution to address data sparsity and cold-start issues by incorporating auxiliary behaviors alongside target behaviors. Howe…
Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty
Peijie Sun, Yifan Wang, Min Zhang +5
With the surge in mobile gaming, accurately predicting user spending on newly downloaded games has become paramount for maximizing revenue. However, the inherently unpredictable na…
Benchmarking Micro-action Recognition: Dataset, Methods, and Applications
Dan Guo, Kun Li, Bin Hu +2
Micro-action is an imperceptible non-verbal behaviour characterised by low-intensity movement. It offers insights into the feelings and intentions of individuals and is important f…
Exploiting Regional Information Transformer for Single Image Deraining
Baiang Li, Zhao Zhang, Huan Zheng +5
Transformer-based Single Image Deraining (SID) methods have achieved remarkable success, primarily attributed to their robust capability in capturing long-range interactions. Howev…
Unified Multi-modal Unsupervised Representation Learning for Skeleton-based Action Understanding
Shengkai Sun, Daizong Liu, Jianfeng Dong +5
Unsupervised pre-training has shown great success in skeleton-based action understanding recently. Existing works typically train separate modality-specific models, then integrate…
Embedded Heterogeneous Attention Transformer for Cross-lingual Image Captioning
Zijie Song, Zhenzhen Hu, Yuanen Zhou +3
Cross-lingual image captioning is a challenging task that requires addressing both cross-lingual and cross-modal obstacles in multimedia analysis. The crucial issue in this task is…
A Survey on Video Moment Localization
Meng Liu, Liqiang Nie, Yunxiao Wang +2
Video moment localization, also known as video moment retrieval, aiming to search a target segment within a video described by a given natural language query. Beyond the task of te…
Vocabulary-informed Zero-shot and Open-set Learning
Yanwei Fu, Xiaomei Wang, Hanze Dong +4
Despite significant progress in object categorization, in recent years, a number of important challenges remain; mainly, the ability to learn from limited labeled data and to recog…
Diversifying Inference Path Selection: Moving-Mobile-Network for Landmark Recognition
Biao Qian, Yang Wang, Zhao Zhang +3
Deep convolutional neural networks have largely benefited computer vision tasks. However, the high computational complexity limits their real-world applications. To this end, many…
Few-Shot Deep Adversarial Learning for Video-based Person Re-identification
Lin Wu, Yang Wang, Hongzhi Yin +2
Video-based person re-identification (re-ID) refers to matching people across camera views from arbitrary unaligned video footages. Existing methods rely on supervision signals to…
Matrix Completion with Deterministic Sampling: Theories and Methods
Guangcan Liu, Qingshan Liu, Xiao-Tong Yuan +1
In some significant applications such as data forecasting, the locations of missing entries cannot obey any non-degenerate distributions, questioning the validity of the prevalent…