736 citations · 1.1k across the 24 of their papers we have counts for
22 papers · 1 filter
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation
Mingjia Yin, Hao Wang, Xiang Xu +7
The sequential recommendation system has been widely studied for its promising effectiveness in capturing dynamic preferences buried in users' sequential behaviors. Despite the con…
Bi-discriminator Domain Adversarial Neural Networks with Class-Level Gradient Alignment
Chuang Zhao, Hongke Zhao, Hengshu Zhu +4
Unsupervised domain adaptation aims to transfer rich knowledge from the annotated source domain to the unlabeled target domain with the same label space. One prevalent solution is…
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Shukang Yin, Chaoyou Fu, Sirui Zhao +7
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with t…
Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm
Jiatong Li, Qi Liu, Fei Wang +5
Personalized learner modeling using cognitive diagnosis (CD), which aims to model learners' cognitive states by diagnosing learner traits from behavioral data, is a fundamental yet…
Multi-Grained Multimodal Interaction Network for Entity Linking
Pengfei Luo, Tong Xu, Shiwei Wu +3
Multimodal entity linking (MEL) task, which aims at resolving ambiguous mentions to a multimodal knowledge graph, has attracted wide attention in recent years. Though large efforts…
Multi-Dimensional Ability Diagnosis for Machine Learning Algorithms
Qi Liu, Zheng Gong, Zhenya Huang +5
Machine learning algorithms have become ubiquitous in a number of applications (e.g. image classification). However, due to the insufficient measurement of traditional metrics (e.g…
A Solution to CVPR'2023 AQTC Challenge: Video Alignment for Multi-Step Inference
Chao Zhang, Shiwei Wu, Sirui Zhao +2
Affordance-centric Question-driven Task Completion (AQTC) for Egocentric Assistant introduces a groundbreaking scenario. In this scenario, through learning instructional videos, AI…
Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation
Likang Wu, Zhi Li, Hongke Zhao +5
Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.…
Multi-Temporal Relationship Inference in Urban Areas
Shuangli Li, Jingbo Zhou, Ji Liu +3
Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While so…
Description-Enhanced Label Embedding Contrastive Learning for Text Classification
Kun Zhang, Le Wu, Guangyi Lv +6
Text Classification is one of the fundamental tasks in natural language processing, which requires an agent to determine the most appropriate category for input sentences. Recently…
A Survey on Multimodal Large Language Models
Shukang Yin, Chaoyou Fu, Sirui Zhao +4
Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perfor…
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary A. Pardos +5
As AI systems continue to evolve, their rigorous evaluation becomes crucial for their development and deployment. Researchers have constructed various large-scale benchmarks to det…
Social Context-aware GCN for Video Character Search via Scene-prior Enhancement
Wenjun Peng, Weidong He, Derong Xu +3
With the increasing demand for intelligent services of online video platforms, video character search task has attracted wide attention to support downstream applications like fine…
A Survey on Large Language Models for Recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu +9
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recomm…
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design
Zaixi Zhang, Qi Liu, Chee-Kong Lee +2
Designing molecules with desirable physiochemical properties and functionalities is a long-standing challenge in chemistry, material science, and drug discovery. Recently, machine…
Quiz-based Knowledge Tracing
Shuanghong Shen, Enhong Chen, Bihan Xu +4
Knowledge tracing (KT) aims to assess individuals' evolving knowledge states according to their learning interactions with different exercises in online learning systems (OIS), whi…
AU-aware graph convolutional network for Macro- and Micro-expression spotting
Shukang Yin, Shiwei Wu, Tong Xu +3
Automatic Micro-Expression (ME) spotting in long videos is a crucial step in ME analysis but also a challenging task due to the short duration and low intensity of MEs. When solvin…
TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
Mingyue Cheng, Xiaoyu Tao, Zhiding Liu +4
Learning transferable representations from unlabeled time series is crucial for improving performance in data-scarce classification. Existing self-supervised methods often operate…
Federated Nearest Neighbor Machine Translation
Yichao Du, Zhirui Zhang, Bingzhe Wu +3
To protect user privacy and meet legal regulations, federated learning (FL) is attracting significant attention. Training neural machine translation (NMT) models with traditional F…
FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification
Mingyue Cheng, Qi Liu, Zhiding Liu +3
Deep learning-based algorithms, e.g., convolutional networks, have significantly facilitated multivariate time series classification (MTSC) task. Nevertheless, they suffer from the…
A Novel Approach for Auto-Formulation of Optimization Problems
Yuting Ning, Jiayu Liu, Longhu Qin +6
In the Natural Language for Optimization (NL4Opt) NeurIPS 2022 competition, competitors focus on improving the accessibility and usability of optimization solvers, with the aim of…
Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training
Yuting Ning, Zhenya Huang, Xin Lin +4
Understanding mathematical questions effectively is a crucial task, which can benefit many applications, such as difficulty estimation. Researchers have drawn much attention to des…