Paper-Conference

KMF: knowledge-aware multi-faceted representation learning for zero-shot node classification
Recently, Zero-Shot Node Classification (ZNC) has been an emerging and crucial task in graph data analysis. This task aims to predict …
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Using Entropy for Group Sampling in Pairwise Ranking from implicit feedback
In recent years, pairwise methods, such as Bayesian Personalized Ranking (BPR), have gained significant attention in the field of …
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Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense
Federated recommendation (FedRec) can train personalized recommenders without collecting user data, but the decentralized nature makes …
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FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification
Deep learning-based algorithms, e.g., convolutional networks, have significantly facilitated multivariate time series classification …
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Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation
Arena-based evaluation has become a key method for assessing large language models (LLMs) through head-to-head model comparisons, …
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HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation
While Retrieval-Augmented Generation (RAG) has emerged as an effective approach for addressing the knowledge outdating problem in Large …
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Improving Time Series Forecasting via Instance-aware Post-hoc Revision
Time series forecasting plays a vital role in various real-world applications and has attracted significant attention in recent …
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TimeDART: A Diffusion Autoregressive Transformer for Self-supervised Time Series Representation
Self-supervised learning has garnered increasing attention in time series analysis for benefiting various downstream tasks and reducing …
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Visual Autoregressive Modeling for Instruction-Guided Image Editing
Recent advances in diffusion models have brought remarkable visual fidelity to instruction-guided image editing. However, their global …
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