4 citations · 16 across the 29 of their papers we have counts for
4 papers · 1 filter
The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang +3
Understanding in-context learning (ICL) capability that enables large language models (LLMs) to excel in proficiency through demonstration examples is of utmost importance. This im…
Explainable Recommender with Geometric Information Bottleneck
Hanqi Yan, Lin Gui, Menghan Wang +2
Explainable recommender systems can explain their recommendation decisions, enhancing user trust in the systems. Most explainable recommender systems either rely on human-annotated…
Distinguishability Calibration to In-Context Learning
Hongjing Li, Hanqi Yan, Yanran Li +3
Recent years have witnessed increasing interests in prompt-based learning in which models can be trained on only a few annotated instances, making them suitable in low-resource set…
Tracking Brand-Associated Polarity-Bearing Topics in User Reviews
Runcong Zhao, Lin Gui, Hanqi Yan +1
Monitoring online customer reviews is important for business organisations to measure customer satisfaction and better manage their reputations. In this paper, we propose a novel d…