Interests
- Data Mining
- Machine Learning
- Social Network Analysis
- Recommender Systems
Latest
- Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
- TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning
- Position: Beyond Model-Centric Prediction — Agentic Time Series Forecasting
- Hierarchical multimodal llms with semantic space alignment for enhanced time series classification
- Global Structure-aware and Feature-augmented Graph Neural Network for Heterophilic Graphs
- Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
- Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
- TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
- PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature
- MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation
- am-ELO: A Stable Framework for Arena-based LLM Evaluation
- Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables
- Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?
- ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis
- A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions
- A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects
- A Survey on Knowledge-Oriented Retrieval-Augmented Generation
- Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
- InstrucTime: Advancing Time Series Classification with Multimodal Language Modeling
- Recognizing unseen objects via multimodal intensive knowledge graph propagation
- Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform
- Advancing Time Series Classification with Multimodal Language Modeling
- Learning Transferable Time Series Classifier with Cross-Domain Pre-training from Language Model
- Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
- AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
- A general tail item representation enhancement framework for sequential recommendation
- Unlocking the Potential of Large Language Models for Explainable Recommendations
- Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
- Federated News Recommendation with Fine-grained Interpolation and Dynamic Clustering
- Using Entropy for Group Sampling in Pairwise Ranking from implicit feedback
- Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense
- A survey on large language models for recommendation
- Learning the explainable semantic relations via unified graph topic-disentangled neural networks
- FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification
- TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
- Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation
- HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation
- Improving Time Series Forecasting via Instance-aware Post-hoc Revision
- TimeDART: A Diffusion Autoregressive Transformer for Self-supervised Time Series Representation
- Visual Autoregressive Modeling for Instruction-Guided Image Editing