The paper proposes a new method for measuring the novelty of biomedical research by calculating latent distances between knowledge units—specifically MeSH terms—using three types of relationships: network, semantic, and hierarchical. It demonstrates that each relationship captures distinct distances and that combining all three yields a more accurate novelty assessment than existing metrics. Validation on a large PLoS ONE dataset and a H1 Connect dataset shows stronger alignment with peer judgments compared to prior indicators.
By Yi Zhao, Heng Zhang, Yuzhuo Wang, Wenqing Wu, Tong Bao, Chengzhi Zhang
Large language models (LLMs) are widely used to assist writing, but this study shows they alter both tone and meaning of human text. A user study found that heavy LLM use increased neutral essays by nearly 70% and made writers feel less creative and less in their voice. Even when prompted to make only grammar edits, LLMs changed the semantic content of essays and produced AI-generated scientific reviews that were less focused on clarity and significance and scored higher on average.
By Marwa Abdulhai, Isadora White, Yanming Wan, Ibrahim Qureshi, Joel Z. Leibo, Max Kleiman-Weiner, Natasha Jaques
arXiv:2506. 17467v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society.
By Weixin Liang
arXiv:2601. 15485v3 Announce Type: replace-cross Abstract: Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise.
By Yifan Qian, Zhe Wen, Alexander C. Furnas, Yue Bai, Erzhuo Shao, Dashun Wang
arXiv:2609.18697v1 Announce Type: new
Abstract: Historians have reconstructed the twentieth-century transformation of general relativity and gravitation (GRG) at the field level and through individua...
By Raphael Schlattmann, Malte Vogl
arXiv:2606.22342v2 Announce Type: replace
Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts....
By Abdul Muntakim, Md Abdullah Al Hafiz Khan, Sadid Hasan, Yong Pei
arXiv:2607. 21327v1 Announce Type: cross Abstract: Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics, yet suffer from temporal lag, semantic shallowness, and an inability to capture the non-linear dynamics of contemporary knowledge ecosystems.
By Muhsen Hammoud
arXiv:2608. 19230v1 Announce Type: cross Abstract: As language models move from drafting prose to running literature-search agents with tool calls, fabricated references are becoming easier to catch and constrain.
By Sina Alemohammad, Denghui Zhang, Bolong Tang, Anthony Qin, Gengchen Mai, Ahmed Abbasi, Richard Baraniuk, Zhangyang Wang
arXiv:2609.16856v1 Announce Type: cross
Abstract: English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by voluntee...
By Neal Reeves, Maja \'Swieczkowska, Amy Rechkemmer, Elena Simperl
How does research evolve, and what substrate would let us forecast where it goes next? Scientific progress is not simply a uniform accumulation of facts: ideas extend prior methods, address known limitations, realize proposed future directions, and sometimes dispute earlier claims.
arXiv:2609.35845v1 Announce Type: cross
Abstract: Macroeconomic productivity metrics, such as Total Factor Productivity, register technological breakthroughs with multi-year reporting lags due to adm...
By Muhammad Sukri Bin Ramli
arXiv:2607. 05401v1 Announce Type: cross Abstract: A small number of methodological contributions, including word2vec, the Transformer, large-scale pre-training, and reinforcement learning from human feedback, have reshaped NLP and AI research over the past decade.
By Fan Huang