4 papers
MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers
Fang Guo, Wenyu Li, Honglei Zhuang +5
The most recent pointwise Large Language Model (LLM) rankers have achieved remarkable ranking results. However, these rankers are hindered by two major drawbacks: (1) they fail to…
XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learners
Yun Luo, Zhen Yang, Fandong Meng +5
Active learning (AL), which aims to construct an effective training set by iteratively curating the most formative unlabeled data for annotation, has been widely used in low-resour…
Task Calibration: Calibrating Large Language Models on Inference Tasks
Yingjie Li, Yun Luo, Xiaotian Xie +1
Large language models (LLMs) have exhibited impressive zero-shot performance on inference tasks. However, LLMs may suffer from spurious correlations between input texts and output…
A Rationale-centric Counterfactual Data Augmentation Method for Cross-Document Event Coreference Resolution
Bowen Ding, Qingkai Min, Shengkun Ma +3
Based on Pre-trained Language Models (PLMs), event coreference resolution (ECR) systems have demonstrated outstanding performance in clustering coreferential events across document…