Scholar assessment plays a fundamental role in faculty recruitment, funding allocation, academic promotion, and talent discovery. Existing scholar assessment methods predominantly rely on bibliometric indicators and reputation proxies, while recent large language model (LLM)-based approaches mainly focus on evaluating individual research papers rather than comprehensively assessing scholars.
arXiv:2606. 26449v1 Announce Type: cross Abstract: Retrieval-augmented systems routinely present citations alongside generated answers, yet a citation does not confirm that the corresponding source meaningfully shaped the output.
By Mohammad Faizan, Dalal Alharthi
arXiv:2605.30947v4 Announce Type: replace
Abstract: LLM-based research agents have advanced rapidly in science and engineering, where research is organized around executable experiments, code, and qu...
By Yating Pan, Jiajun Zhang, Jun Wang, Qi Su
arXiv:2607. 16989v1 Announce Type: cross Abstract: Introduction.
By Mohammad Arvan, Amber E. Osterholt, Bailee Rue, Yuvaneswaren Ramakrishnan Sureshbabu, Krishna Riteshkumar Patel, Rebecca T. Feinstein, Bethany C. Bray, Niranjan S. Karnik
arXiv:2606. 24894v2 Announce Type: replace-cross Abstract: Large language models have shown strong fluency in scientific writing, yet the evaluation of related work generation (RWG) remains limited.
By Anzhe Xie, Weihang Su, Jiaxin Mao, Yiqun Liu, Shaoping Ma, Qingyao Ai
arXiv:2609.23735v2 Announce Type: new
Abstract: Scientific agents support a range of literature-based research tasks, such as retrieval, question answering, evidence-grounded generation, and claim as...
By ScholarSeed AI Team, Caoqinwei Gong, Xue Jiang, Wei Luo, Xiaoyu Qiu, Jiayi Sheng, Yi Wang, Zheng Yu, Ao Zhang, Haifan Zhang, Hanwei Zhang, Jihai Zhang, Yuan Cao, Wei Chen, Liyun Dai, Wenkai Fang, Guanglei Wang, Kai Ying, Tingyu Zhu, Wotao Yin
arXiv:2608.21374v1 Announce Type: new
Abstract: Literature reviews are essential to scientific progress, but rigorously evaluating automatically generated reviews remains difficult because many aspec...
By Ruotong Zhao, Zhiyu Chen, Xurui Liu, Haidong Xue, Dong Liang, Jigao Fu, Wu YanBiao, Yuanyi Zhen, Fengli Xu, Yong Li
arXiv:2608.28612v1 Announce Type: new
Abstract: Generating professional scholarly content, such as peer reviews and rebuttals, requires an intricate synergy between domain reasoning and factual groun...
By Xuerui Su, Liya Guo, Qizhi Pei, Qipeng Guo, Zhongbo Tian, Lijun Wu, Kai Chen, Zun Wang
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:2605.29522v2 Announce Type: replace
Abstract: As scientific literature grows rapidly and research increasingly involves AI agents, automated survey generation has become a key capability for bo...
By Ziyue Yang, Da Ma, Hanqi Li, Zijian Wang, Tiancheng Huang, Zijian Hu, Chenrun Wang, Yunzhe Zhang, Xiaobao Wu, Kai Yu, Lu Chen
arXiv:2607. 12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human sees, making that parametric corpus presence a measurement problem.
By Bojie Li, Noah Shi
arXiv:2607. 22684v1 Announce Type: cross Abstract: Artificial intelligence systems increasingly mediate how science is found and credited.
By Aadi Narayana Varma Dantuluri, Sushrut Thorat, Paras Chopra