Tag
This paper explores using lightweight webcam-based eye-tracking features to improve keyphrase extraction from Chinese academic abstracts, introducing the CLIS-ET corpus and showing that fixation features enhance KPE performance.
This paper investigates whether EEG signals can complement eye-tracking signals for automatic keyphrase extraction from microblogs. Using the ZuCo corpus, the authors show that cognitive signals, especially EEG, improve AKE performance across different models.
This paper proposes an attention expansion mechanism to enhance keyphrase extraction from long documents by augmenting PLM token representations with out-of-context information, achieving consistent improvements over state-of-the-art models without requiring full-document attention or expensive LLM inference.