2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CL2025
Surprise Calibration for Better In-Context Learning
Zhihang Tan, Jingrui Hou, Ping Wang +2
In-context learning (ICL) has emerged as a powerful paradigm for task adaptation in large language models (LLMs), where models infer underlying task structures from a few demonstra…
cs.IR2023
Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluation
Jingrui Hou, Georgina Cosma, Axel Finke
Continual learning refers to the capability of a machine learning model to learn and adapt to new information, without compromising its performance on previously learned tasks. Alt…
cs.CL2023★ 2 cited
ArcGPT: A Large Language Model Tailored for Real-world Archival Applications
Shitou Zhang, Jingrui Hou, Siyuan Peng +3
Archives play a crucial role in preserving information and knowledge, and the exponential growth of such data necessitates efficient and automated tools for managing and utilizing…