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09/08/2023
Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese
Large Language Models (LLMs) have demonstrated remarkable success in div...
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07/08/2023
SDT: A Low-cost and Topology-reconfigurable Testbed for Network Research
Network experiments are essential to network-related scientific research...
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06/25/2023
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
Learning Granger causality from event sequences is a challenging but ess...
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07/12/2022
Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is a core task for high-level i...
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06/11/2022
Federated Learning with GAN-based Data Synthesis for Non-IID Clients
Federated learning (FL) has recently emerged as a popular privacy-preser...
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05/07/2022
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance
Domain adaptation on time-series data is often encountered in the indust...
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05/03/2022
HL-Net: Heterophily Learning Network for Scene Graph Generation
Scene graph generation (SGG) aims to detect objects and predict their pa...
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01/13/2022
REST: Debiased Social Recommendation via Reconstructing Exposure Strategies
The recommendation system, relying on historical observational data to m...
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12/30/2021
Motif Graph Neural Network
Graphs can model complicated interactions between entities, which natura...
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11/14/2021
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations
Sequential recommendation aims to choose the most suitable items for a u...
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11/05/2021
Transferable Time-Series Forecasting under Causal Conditional Shift
This paper focuses on the problem of semi-supervised domain adaptation f...
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06/14/2021
Graph Domain Adaptation: A Generative View
Recent years have witnessed tremendous interest in deep learning on grap...
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05/09/2021
Aggregating From Multiple Target-Shifted Sources
Multi-source domain adaptation aims at leveraging the knowledge from mul...
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12/22/2020
Learning Disentangled Semantic Representation for Domain Adaptation
Domain adaptation is an important but challenging task. Most of the exis...
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12/22/2020
Semi-Supervised Disentangled Framework for Transferable Named Entity Recognition
Named entity recognition (NER) for identifying proper nouns in unstructu...
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12/22/2020
Time Series Domain Adaptation via Sparse Associative Structure Alignment
Domain adaptation on time series data is an important but challenging ta...
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05/06/2020
TAG : Type Auxiliary Guiding for Code Comment Generation
Existing leading code comment generation approaches with the structure-t...
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11/30/2019
Disentanglement Challenge: From Regularization to Reconstruction
The challenge of learning disentangled representation has recently attra...
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10/13/2019
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems
Data-driven models are becoming essential parts in modern mechanical sys...
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11/16/2017
An Encoder-Decoder Framework Translating Natural Language to Database Queries
Machine translation is going through a radical revolution, driven by the...
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06/17/2017