7 papers
FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents
Jia Deng, Yimeng Chen, Xiaoqing Xiang +9
Training deep search agents requires verifiable questions whose answers remain unavailable until sufficient evidence has been acquired through search. Existing synthesis methods of…
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…
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…
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…
Jasper-Token-Compression-600M Technical Report
Dun Zhang, Ziyang Zeng, Yudong Zhou +1
This technical report presents the training methodology and evaluation results of the open-source Jasper-Token-Compression-600M model, released in November 2025. Building on previo…
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…