3 citations · 7 across the 5 of their papers we have counts for
5 papers
Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers
Weiwei Sun, Zheng Chen, Xinyu Ma +6
Recent studies have demonstrated the great potential of Large Language Models (LLMs) serving as zero-shot relevance rankers. The typical approach involves making comparisons betwee…
Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval
Xiaojie Sun, Keping Bi, Jiafeng Guo +5
Grounded on pre-trained language models (PLMs), dense retrieval has been studied extensively on plain text. In contrast, there has been little research on retrieving data with mult…
On the Security Bootstrapping in Named Data Networking
Tianyuan Yu, Xinyu Ma, Hongcheng Xie +2
By requiring all data packets been cryptographically authenticatable, the Named Data Networking (NDN) architecture design provides a basic building block for secured networking. Th…
Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset
Liantao Ma, Chaohe Zhang, Junyi Gao +8
Objective: Peritoneal Dialysis (PD) is one of the most widely used life-supporting therapies for patients with End-Stage Renal Disease (ESRD). Predicting mortality risk and identif…
MedFACT: Modeling Medical Feature Correlations in Patient Health Representation Learning via Feature Clustering
Xinyu Ma, Xu Chu, Yasha Wang +4
In healthcare prediction tasks, it is essential to exploit the correlations between medical features and learn better patient health representations. Existing methods try to estima…