5 citations · 8 across the 8 of their papers we have counts for
8 papers
Large language models improve Alzheimer's disease diagnosis using multi-modality data
Yingjie Feng, Jun Wang, Xianfeng Gu +2
In diagnosing challenging conditions such as Alzheimer's disease (AD), imaging is an important reference. Non-imaging patient data such as patient information, genetic data, medica…
Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!
Zecheng Tang, Pinzheng Wang, Keyan Zhou +3
Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space. However, there exist nonnegligible gaps between tra…
Test-Time Adaptation with Perturbation Consistency Learning
Yi Su, Yixin Ji, Juntao Li +2
Currently, pre-trained language models (PLMs) do not cope well with the distribution shift problem, resulting in models trained on the training set failing in real test scenarios.…
Intent-aware Ranking Ensemble for Personalized Recommendation
Jiayu Li, Peijie Sun, Zhefan Wang +5
Ranking ensemble is a critical component in real recommender systems. When a user visits a platform, the system will prepare several item lists, each of which is generally from a s…
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening
Min Cao, Yang Bai, Jingyao Wang +3
Under the flourishing development in performance, current image-text retrieval methods suffer from -related time complexity, which hinders their application in practice. Targeti…
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting
Hongyao Tang, Min Zhang, Jianye Hao
Knowing the learning dynamics of policy is significant to unveiling the mysteries of Reinforcement Learning (RL). It is especially crucial yet challenging to Deep RL, from which th…