Interests
- Agentic AI
- Time Series Analysis
- Tabular Data Mining
- 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
- From Hypothesis to Premises: LLM-based Backward Logical Reasoning with Selective Symbolic Translation
- STaR: Towards Cognitive Table Reasoning via Slow-Thinking Large Language Models
- A Hybrid Multi-Factor Framework for Dynamic Intraoperative Hypotension Prediction
- Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting
- Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner
- 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
- Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce
- PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature
- MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation
- Tag-augmented Dual-target Cross-domain Recommendation
- Preference Trajectory Modeling via Flow Matching for Sequential Recommendation
- 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
- 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
- Generative Pretrained Hierarchical Transformer for Time Series Forecasting
- Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
- BLADE: A Behavior-Level Data Augmentation Framework with Dual Fusion Modeling for Multi-Behavior Sequential Recommendation
- 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
- 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