49 citations · 54 across the 18 of their papers we have counts for
18 papers
SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models
Feng Wu, Harsh Deep, Eric Lehman +5
Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, multichannel signal complexity, inherent…
SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering
Yuqing Fu, Yimin Deng, Wanyu Wang +9
Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to th…
MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning
Yimin Deng, Zhenxi Lin, Yejing Wang +9
Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While Large Language Models (LLMs) have shown strong capabilities in commonsense reasoni…
AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models
Yimin Deng, Yejing Wang, Zhenxi Lin +8
Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle temporal information remains limited…
Enhancing Conversational Agents via Task-Oriented Adversarial Memory Adaptation
Yimin Deng, Yuqing Fu, Derong Xu +10
Conversational agents struggle to handle long conversations due to context window limitations. Therefore, memory systems are developed to leverage essential historical information.…
Exploring Spectral Characteristics for Single Image Reflection Removal
Pengbo Guo, Chengxu Liu, Guoshuai Zhao +3
Eliminating reflections caused by incident light interacting with reflective medium remains an ill-posed problem in the image restoration area. The primary challenge arises from th…
A Plug-and-play Model-agnostic Embedding Enhancement Approach for Explainable Recommendation
Yunqi Mi, Boyang Yan, Guoshuai Zhao +2
Existing multimedia recommender systems provide users with suggestions of media by evaluating the similarities, such as games and movies. To enhance the semantics and explainabilit…
Federated Consistency- and Complementarity-aware Consensus-enhanced Recommendation
Yunqi Mi, Boyang Yan, Guoshuai Zhao +2
Personalized federated recommendation system (FedRec) has gained significant attention for its ability to preserve privacy in delivering tailored recommendations. To alleviate the…
A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions
Yunqi Mi, Jiakui Shen, Guoshuai Zhao +2
Extending recommender systems to federated learning (FL) frameworks to protect the privacy of users or platforms while making recommendations has recently gained widespread attenti…
A Model-agnostic Strategy to Mitigate Embedding Degradation in Personalized Federated Recommendation
Jiakui Shen, Yunqi Mi, Guoshuai Zhao +2
Centralized recommender systems encounter privacy leakage due to the need to collect user behavior and other private data. Hence, federated recommender systems (FedRec) have become…
A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs
Yimin Deng, Yuxia Wu, Yejing Wang +9
Temporal knowledge graph reasoning aims to predict future events with knowledge of existing facts and plays a key role in various downstream tasks. Previous methods focused on eith…
Neighborhood Commonality-aware Evolution Network for Continuous Generalized Category Discovery
Ye Wang, Yaxiong Wang, Guoshuai Zhao +1
Continuous Generalized Category Discovery (C-GCD) aims to continually discover novel classes from unlabelled image sets while maintaining performance on old classes. In this paper,…
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent Discovery
Yimin Deng, Yuxia Wu, Guoshuai Zhao +2
New intent discovery is a crucial capability for task-oriented dialogue systems. Existing methods focus on transferring in-domain (IND) prior knowledge to out-of-domain (OOD) data…
Knowledge Adaptation Network for Few-Shot Class-Incremental Learning
Ye Wang, Yaxiong Wang, Guoshuai Zhao +1
Few-shot class-incremental learning (FSCIL) aims to incrementally recognize new classes using a few samples while maintaining the performance on previously learned classes. One of…
Knowledge Transfer-Driven Few-Shot Class-Incremental Learning
Ye Wang, Yaxiong Wang, Guoshuai Zhao +1
Few-shot class-incremental learning (FSCIL) aims to continually learn new classes using a few samples while not forgetting the old classes. The key of this task is effective knowle…
Logic Diffusion for Knowledge Graph Reasoning
Xiaoying Xie, Biao Gong, Yiliang Lv +3
Most recent works focus on answering first order logical queries to explore the knowledge graph reasoning via multi-hop logic predictions. However, existing reasoning models are li…
A Neural Corpus Indexer for Document Retrieval
Yujing Wang, Yingyan Hou, Haonan Wang +13
Current state-of-the-art document retrieval solutions mainly follow an index-retrieve paradigm, where the index is hard to be directly optimized for the final retrieval target. In…
Multi-Sample based Contrastive Loss for Top-k Recommendation
Hao Tang, Guoshuai Zhao, Yuxia Wu +1
The top-k recommendation is a fundamental task in recommendation systems which is generally learned by comparing positive and negative pairs. The Contrastive Loss (CL) is the key i…