DH학술

https://arxiv.org/abs/2501.09751 https://github.com/zjunlp/OmniThink Machine writing with large language models often relies on retrieval-augmented generation. However, these approaches remain confined within the boundaries of the model’s predefined scope, limiting the generation of content with rich information. Specifically, vanilla-retrieved information tends to lack depth, utility, and suffers from redundancy, which negatively impacts the quality of generated articles, leading … Read more

https://arxiv.org/abs/2501.09891 We explore an evolutionary search strategy for scaling inference time compute in Large Language Models. The proposed approach, Mind Evolution, uses a language model to generate, recombine and refine candidate responses. The proposed approach avoids the need to formalize the underlying inference problem whenever a solution evaluator is available. Controlling for inference cost, we … Read more

The New Calculator? Practices, Norms, and Implications of Generative AI in Higher Education. https://arxiv.org/abs/2501.08864 Simkute 외(2025)의 논문에서는 고등 교육에서 생성형 AI(GenAI)의 사용 현황, 규범, 그리고 그 영향에 대한 심층적인 연구를 수행했습니다. 본 연구는 2023년 12월부터 2024년 2월까지 영국 내 두 개 대학의 다양한 학과 학생 26명과 교수 11명을 대상으로 반 구조화된 인터뷰를 통해 진행되었습니다.   … Read more

https://arxiv.org/abs/2501.11951 Hanja Processing Platform: https://hanja.dev YouTube: HERITAGE: An End-to-End Web Platform for Processing Korean Historical Documents in Hanja Seyoung Song, Haneul Yoo, Jiho Jin, Kyunghyun Cho, Alice Oh While Korean historical documents are invaluable cultural heritage, understanding those documents requires in-depth Hanja expertise. Hanja is an ancient language used in Korea before the 20th century, whose characters were borrowed … Read more