2 citations · 3 across the 6 of their papers we have counts for
6 papers
LLM-Oriented Information Retrieval: A Denoising-First Perspective
Lu Dai, Liang Sun, Fanpu Cao +4
Modern information retrieval (IR) is no longer consumed primarily by humans but increasingly by large language models (LLMs) via retrieval-augmented generation (RAG) and agentic se…
When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs
Fanpu Cao, Xin Zou, Xuming Hu +1
Multimodal large language models (MLLMs) have become a key interface for visual reasoning and grounded question answering, yet they remain vulnerable to visual hallucinations, wher…
Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
Fanpu Cao, Lu Dai, Jindong Han +1
Multivariate time series forecasting (MTSF) plays a vital role in numerous real-world applications, yet existing models remain constrained by their reliance on a limited historical…
ProCache: Constraint-Aware Feature Caching with Selective Computation for Diffusion Transformer Acceleration
Fanpu Cao, Yaofo Chen, Zeng You +1
Diffusion Transformers (DiTs) have achieved state-of-the-art performance in generative modeling, yet their high computational cost hinders real-time deployment. While feature cachi…
SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series Forecasting
Wenxuan Xie, Fanpu Cao
In recent work on time-series prediction, Transformers and even large language models have garnered significant attention due to their strong capabilities in sequence modeling. How…
Ister: Linear Transformer for Efficient Multivariate Time Series Forecasting
Fanpu Cao, Shu Yang, Zhengjian Chen +2
Transformer-based models have achieved remarkable success in multivariate time series forecasting (MTSF) by capturing long-range dependencies. However, their widespread adoption is…