Zhichao Xu

Reinforcement Learning to Rank Using Coarse-grained Rewards

2022 · arXiv (Cornell University)

Learning to rank (LTR) plays a crucial role in various Information Retrieval (IR) tasks. Although supervised LTR methods based on fine-grained relevance labels (e.g., document-level annotations) have achieved significant success, their reliance on costly and …

RankMamba: Benchmarking Mamba's Document Ranking Performance in the Era of Transformers

2024 · arXiv (Cornell University)

Transformer structure has achieved great success in multiple applied machine learning communities, such as natural language processing (NLP), computer vision (CV) and information retrieval (IR). Transformer architecture's core mechanism\, -- \,attention requires $O(n^2)$ time complexity …

Improved Deep Support Vector Data Description Model Using Feature Patching for Industrial Anomaly Detection

2024 · Sensors

In industrial contexts, anomaly detection is crucial for ensuring quality control and maintaining operational efficiency in manufacturing processes. Leveraging high-level features extracted from ImageNet-trained networks and the robust capabilities of the Deep Support Vector Data …

CSPLADE: Learned Sparse Retrieval with Causal Language Models

2025 · arXiv (Cornell University)

In recent years, dense retrieval has been the focus of information retrieval (IR) research. While effective, dense retrieval produces uninterpretable dense vectors, and suffers from the drawback of large index size. Learned sparse retrieval (LSR) …