4 citations · 7 across the 13 of their papers we have counts for
13 papers
SIVF: GPU-Resident IVF Index for Streaming Vector Search
Dongfang Zhao
GPU-accelerated Inverted File (IVF) index is one of the industry standards for large-scale vector search but relies on static VRAM layouts that hinder real-time mutability. Our ben…
MCGI: Manifold-Consistent Graph Indexing for Billion-Scale Disk-Resident Vector Search
Dongfang Zhao
Graph-based Approximate Nearest Neighbor (ANN) search often suffers from performance degradation in high-dimensional spaces due to the Euclidean-Geodesic mismatch, where greedy rou…
ProHD: Projection-Based Hausdorff Distance Approximation
Jiuzhou Fu, Luanzheng Guo, Nathan R. Tallent +1
The Hausdorff distance (HD) is a robust measure of set dissimilarity, but computing it exactly on large, high-dimensional datasets is prohibitively expensive. We propose \textbf{Pr…
On The Reproducibility Limitations of RAG Systems
Baiqiang Wang, Dongfang Zhao, Nathan R Tallent +1
Retrieval-Augmented Generation (RAG) is increasingly employed in generative AI-driven scientific workflows to integrate rapidly evolving scientific knowledge bases, yet its reliabi…
PIR-RAG: A System for Private Information Retrieval in Retrieval-Augmented Generation
Baiqiang Wang, Qian Lou, Mengxin Zheng +1
Retrieval-Augmented Generation (RAG) has become a foundational component of modern AI systems, yet it introduces significant privacy risks by exposing user queries to service provi…
TokenBlowUp: Resolving Representational Singularities in LLM Token Spaces via Monoidal Transformations
Dongfang Zhao
Recent work has provided compelling evidence challenging the foundational manifold hypothesis for the token embedding spaces of Large Language Models (LLMs). These findings reveal…
HybHuff: Lossless Compression for Hypergraphs via Entropy-Guided Huffman-Bitwise Coordination
Tianyu Zhao, Dongfang Zhao, Luanzheng Guo +1
Hypergraphs provide a natural representation for many-to-many relationships in data-intensive applications, yet their scalability is often hindered by high memory consumption. Whil…
Privacy-Preserving Hamming Distance Computation with Property-Preserving Hashing
Dongfang Zhao
We study the problem of approximating Hamming distance in sublinear time under property-preserving hashing (PPH), where only hashed representations of inputs are available. Buildin…
Approximate Hausdorff Distance for Multi-Vector Databases
Dongfang Zhao
The Hausdorff distance is a fundamental measure for comparing sets of vectors, widely used in database theory and geometric algorithms. However, its exact computation is computatio…
Ares: Approximate Representations via Efficient Sparsification -- A Stateless Approach through Polynomial Homomorphism
Dongfang Zhao
The increasing prevalence of high-dimensional data demands efficient and scalable compression methods to support modern applications. However, existing techniques like PCA and Auto…
Approximate Fiber Product: A Preliminary Algebraic-Geometric Perspective on Multimodal Embedding Alignment
Dongfang Zhao
Multimodal tasks, such as image-text retrieval and generation, require embedding data from diverse modalities into a shared representation space. Aligning embeddings from heterogen…
EnviroExam: Benchmarking Environmental Science Knowledge of Large Language Models
Yu Huang, Liang Guo, Wanqian Guo +4
In the field of environmental science, it is crucial to have robust evaluation metrics for large language models to ensure their efficacy and accuracy. We propose EnviroExam, a com…
Enhancing Data Provenance and Model Transparency in Federated Learning Systems -- A Database Approach
Michael Gu, Ramasoumya Naraparaju, Dongfang Zhao
Federated Learning (FL) presents a promising paradigm for training machine learning models across decentralized edge devices while preserving data privacy. Ensuring the integrity a…