charactER Representation

Character representation in natural language processing focuses on developing computational methods to effectively capture and utilize information about characters within narratives, aiming to improve understanding and generation of stories. Current research emphasizes creating richer, more nuanced character representations using techniques like graph-based methods, large language models (LLMs) for information extraction and validation, and contrastive learning to improve consistency across different contexts. These advancements are significant for improving story generation, analyzing literary works, and understanding how character portrayals evolve across different communities and media, impacting fields from digital storytelling to literary analysis.