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20192026
most citedSPFresh: Incremental In-Place Update for Billion-Scale Vector Search

58 citations · 110 across the 67 of their papers we have counts for

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5 papers · 1 filter

cs.IR2026

PosIR: Position-Aware Heterogeneous Information Retrieval Benchmark

Ziyang Zeng, Dun Zhang, Yu Yan +4

In real-world documents, the information relevant to a user query may reside anywhere from the beginning to the end. This makes position bias -- a systematic tendency of retrieval…

cs.IR2025

Optimizing Generative Ranking Relevance via Reinforcement Learning in Xiaohongshu Search

Ziyang Zeng, Heming Jing, Jindong Chen +11

Ranking relevance is a fundamental task in search engines, aiming to identify the items most relevant to a given user query. Traditional relevance models typically produce scalar s…

cs.IR2025

An Empirical Study of Position Bias in Modern Information Retrieval

Ziyang Zeng, Dun Zhang, Jiacheng Li +3

This study investigates the position bias in information retrieval, where models tend to overemphasize content at the beginning of passages while neglecting semantically relevant i…

cs.IR2025

A Zero-shot Explainable Doctor Ranking Framework with Large Language Models

Ziyang Zeng, Dongyuan Li, Yuqing Yang

Online medical service provides patients convenient access to doctors, but effectively ranking doctors based on specific medical needs remains challenging. Current ranking approach…

cs.IR2024

SPFresh: Incremental In-Place Update for Billion-Scale Vector Search

Yuming Xu, Hengyu Liang, Jin Li +9

Approximate Nearest Neighbor Search (ANNS) is now widely used in various applications, ranging from information retrieval, question answering, and recommendation, to search for sim…