arXiv:2609.22104v1 Announce Type: new
Abstract: As automated scientific discovery advances, Large Language Models (LLMs) can now generate research ideas at an unprecedented scale, shifting the bottle...
By Rongcan Pei, Fang Guo, Qinglin Qi, Qi Zhu, Yun Luo, Jianhao Yan, Minjun Zhu, Qiujie Xie, Dehong Zheng, Yue Zhang
arXiv:2608. 13136v1 Announce Type: cross Abstract: With the rapid advancement of large language models (LLMs), research idea generation has attracted increasing attention.
By Chenrun Wang, Mingxuan Zhu, Tiancheng Huang, Wenjie Li, Yujie Zhang, Zichen Zhu, Zhiying Zou, Kai Yu, Lu Chen
The paper introduces SciMuse, an AI system that generates personalized research ideas by combining a knowledge graph of 58 million papers with a large language model. A large-scale evaluation involving over 100 research group leaders across disciplines rated more than 4,400 ideas, yielding modest overall interest scores but showing that 24.9% were rated highly. The study also demonstrates that graph-derived features can predict idea interest and can be used to control idea properties, offering a new methodology for generating and assessing scientific ideas.
By Xuemei Gu, Mario Krenn
IDEAlign introduces a new protocol for evaluating the similarity of large language model (LLM) annotations to expert judgments. It uses pick‑the‑odd‑one‑out tasks to capture expert similarity and benchmarks various similarity methods—including text embeddings, topic models, and LLM-as-a-judge—against these human ratings. Applied to educational datasets, the study finds that most metrics miss nuanced expert dimensions, with LLM-as-a-judge performing best yet still insufficient for full expert alignment.
By Hyunji Nam, Lucia Langlois, James Malamut, Mei Tan, Dorottya Demszky
Large language models (LLMs) have achieved remarkable progress in language understanding, reasoning, and generation, sparking growing interest in their creative potential. Realizing this potential requires systematic and scalable methods for evaluating creativity across diverse tasks.
arXiv:2606. 07226v1 Announce Type: cross Abstract: Human creativity has emerged as a critical competency in the era of large language models.
By Tongzhou Yu, Mingjia Li, Hong Qian, Wenkai Wang, Zongbao Zhang, Yaoyu Jiang, Xiangfeng Wang, Aimin Zhou, Jiajun Guo