Fetching the paper…
Reading the bibliography…
Recent advancements in large language models (LLMs) have achieved promising performances across various applications.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W Cohen, and Xinghua Lu. 2019 · 1909
Earlier work this paper cites.
Amyloid plaque core protein in alzheimer disease and down syndrome
C L Masters, G Simms, N A Weinman, G Multhaup, B L McDonald, and K Beyreuther. 1985 · 1985
Earlier work this paper cites.
Wordnet: a lexical database for english
George A Miller. 1995 · 1995
Earlier work this paper cites.
Qa4mre 2011-2013: Overview of question answering for machine reading evaluation
Anselmo Peñas, Eduard H. Hovy, Pamela Forner, Álvaro Rodrigo, Richard F. E. Sutcliffe, and Roser Morante. 2013 · 2013
Earlier work this paper cites.
Pubtator: a web-based text mining tool for assisting biocuration
Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2013 · 2013
Earlier work this paper cites.
Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
Earlier work this paper cites.
Systematic integration of biomedical knowledge prioritizes drugs for repurposing
Daniel Scott Himmelstein, Antoine Lizee, Christine Hessler, Leo Brueggeman, Sabrina L Chen, Dexter Hadley, Ari Green, Pouya Khankhanian, and Sergio E Baranzini. 2017 · 2017
Earlier work this paper cites.
Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
To BERT or not to BERT: Comparing Speech and Language-Based Approaches for Alzheimer’s Disease Detection
Aparna Balagopalan, Benjamin Eyre, Frank Rudzicz, and Jekaterina Novikova. 2020 · 2020
Earlier work this paper cites.
Aser: A large-scale eventuality knowledge graph
Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung. 2020 · 2020
Earlier work this paper cites.
Discos: bridging the gap between discourse knowledge and commonsense knowledge
Tianqing Fang, Hongming Zhang, Weiqi Wang, Yangqiu Song, and Bin He. 2021 · 2021
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al. 2021 · 2021
Earlier work this paper cites.
What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2021 · 2021
Earlier work this paper cites.
Predicting dementia from spontaneous speech using large language models
Felix Agbavor and Hualou Liang. 2022 · 2022
Earlier work this paper cites.
C3kg: A chinese commonsense conversation knowledge graph
Dawei Li, Yanran Li, Jiayi Zhang, Ke Li, Chen Wei, Jianwei Cui, and Bin Wang. 2022 · 2022
Earlier work this paper cites.
Mining on alzheimer’s diseases related knowledge graph to identity potential ad-related semantic triples for drug repurposing
Yi Nian, Xinyue Hu, Rui Zhang, Jingna Feng, Jingcheng Du, Fang Li, Yong Chen, and Cui Tao. 2022 · 2022
Earlier work this paper cites.
Introducing chatgpt
OpenAI. 2022 · 2022
Earlier work this paper cites.
Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu. 2022 · 2022
Earlier work this paper cites.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Earlier work this paper cites.
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
Earlier work this paper cites.
Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al. 2023 · 2023
Earlier work this paper cites.
Graph of thoughts: Solving elaborate problems with large language models
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Michal Podstawski, Hubert Niewiadomski, Piotr Nyczyk, et al. 2023 · 2023
Earlier work this paper cites.
Iterative zero-shot llm prompting for knowledge graph construction
Salvatore Carta, Alessandro Giuliani, Leonardo Piano, Alessandro Sebastian Podda, Livio Pompianu, and Sandro Gabriele Tiddia. 2023 · 2023
Earlier work this paper cites.
Meditron-70b: Scaling medical pretraining for large language models
Zeming Chen, Alejandro Hernández Cano, Angelika Romanou, Antoine Bonnet, Kyle Matoba, Francesco Salvi, Matteo Pagliardini, Simin Fan, Andreas Köpf, Amirkeivan Mohtashami, et al. 2023 · 2023
Cited alongside, same era.
In silico drug repurposing using knowledge graph embeddings for alzheimer’s disease
Geesa Daluwatumulle, Rupika Wijesinghe, and Ruvan Weerasinghe. 2023 · 2023
Cited alongside, same era.
Large language models improve alzheimer’s disease diagnosis using multi-modality data
Yingjie Feng, Xiaoyin Xu, Yueting Zhuang, and Min Zhang. 2023 · 2023
Cited alongside, same era.
Pive: Prompting with iterative verification improving graph-based generative capability of llms
Jiuzhou Han, Nigel Collier, Wray Buntine, and Ehsan Shareghi. 2023 · 2023
Cited alongside, same era.
Synthesize heterogeneous biological knowledge via representation learning for alzheimer’s disease drug repurposing
Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models
Yilin Wen, Zifeng Wang, and Jimeng Sun. 2023 · 2023
Later among the works it cites.
TILP: Differentiable learning of temporal logical rules on knowledge graphs
Siheng Xiong, Yuan Yang, Faramarz Fekri, and James Clayton Kerce. 2023 · 2023
Later among the works it cites.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L Griffiths, Yuan Cao, and Karthik Narasimhan. 2023 · 2023
Later among the works it cites.
Chain-of-note: Enhancing robustness in retrieval-augmented language models
Wenhao Yu, Hongming Zhang, Xiaoman Pan, Kaixin Ma, Hongwei Wang, and Dong Yu. 2023 · 2023
Later among the works it cites.
Chatdoctor: A medical chat model fine-tuned on llama model using medical domain knowledge
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Kang-Lin Hsieh, German Plascencia-Villa, Ko-Hong Lin, George Perry, Xiaoqian Jiang, and Yejin Kim. 2023 · 2023
Cited alongside, same era.
Structgpt: A general framework for large language model to reason over structured data
Jinhao Jiang, Kun Zhou, Zican Dong, Keming Ye, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
Cited alongside, same era.
Large language models struggle to learn long-tail knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023
Cited alongside, same era.
Kg-gpt: A general framework for reasoning on knowledge graphs using large language models
Jiho Kim, Yeonsu Kwon, Yohan Jo, and Edward Choi. 2023 · 2023
Cited alongside, same era.
Multi-level contrastive learning for script-based character understanding
Dawei Li, Hengyuan Zhang, Yanran Li, and Shiping Yang. 2023b · 2023
Cited alongside, same era.
Two directions for clinical data generation with large language models: Data-to-label and label-to-data
Rumeng Li, Xun Wang, and Hong Yu. 2023c · 2023
Cited alongside, same era.
Compressing context to enhance inference efficiency of large language models
Yucheng Li, Bo Dong, Frank Guerin, and Chenghua Lin. 2023d · 2023
Cited alongside, same era.
Large language model is not a good few-shot information extractor, but a good reranker for hard samples!
Yubo Ma, Yixin Cao, Yong Hong, and Aixin Sun. 2023 · 2023
Cited alongside, same era.
Li Yunxiang, Li Zihan, Zhang Kai, Dan Ruilong, and Zhang You. 2023 · 2023
Later among the works it cites.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Haotong Zhang, Joseph Gonzalez, and Ion Stoica. 2023 · 2023
Later among the works it cites.
Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities
Yuqi Zhu, Xiaohan Wang, Jing Chen, Shuofei Qiao, Yixin Ou, Yunzhi Yao, Shumin Deng, Huajun Chen, and Ningyu Zhang. 2023 · 2023
Later among the works it cites.
Codekgc: Code language model for generative knowledge graph construction
Zhen Bi, Jing Chen, Yinuo Jiang, Feiyu Xiong, Wei Guo, Huajun Chen, and Ningyu Zhang. 2024 · 2024
Closest in time.
Benchmarking large language models in retrieval-augmented generation
Jiawei Chen, Hongyu Lin, Xianpei Han, and Le Sun. 2024 · 2024
Closest in time.
Construction of hyper-relational knowledge graphs using pre-trained large language models
Preetha Datta, Fedor Vitiugin, Anastasiia Chizhikova, and Nitin Sawhney. 2024 · 2024
Closest in time.
Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, and Sutanay Choudhury. 2024 · 2024
Closest in time.
Biomistral: A collection of open-source pretrained large language models for medical domains
Yanis Labrak, Adrien Bazoge, Emmanuel Morin, Pierre-Antoine Gourraud, Mickael Rouvier, and Richard Dufour. 2024 · 2024
Closest in time.
Contextualization distillation from large language model for knowledge graph completion
Dawei Li, Zhen Tan, Tianlong Chen, and Huan Liu. 2024 · 2024
Closest in time.
Clinfo. ai: An open-source retrieval-augmented large language model system for answering medical questions using scientific literature
Alejandro Lozano, Scott L Fleming, Chia-Chun Chiang, and Nigam Shah. 2023 · 2024
Closest in time.
Knowla: Enhancing parameter-efficient finetuning with knowledgeable adaptation
Xindi Luo, Zequn Sun, Jing Zhao, Zhe Zhao, and Wei Hu. 2024 · 2024
Closest in time.
New embedding models and api updates
OpenAI. 2024 · 2024
Closest in time.
Unifying large language models and knowledge graphs: A roadmap
Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. 2024 · 2024
Closest in time.
Julio C Rangel, Tarcisio Mendes de Farias, Ana Claudia Sima, and Norio Kobayashi. 2024 · 2024
Closest in time.
Large language models for data annotation: A survey
Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, and Huan Liu. 2024 · 2024
Closest in time.
Can llms learn from previous mistakes? investigating llms’ errors to boost for reasoning
Yongqi Tong, Dawei Li, Sizhe Wang, Yujia Wang, Fei Teng, and Jingbo Shang. 2024 · 2024
Closest in time.
How easily do irrelevant inputs skew the responses of large language models?
Siye Wu, Jian Xie, Jiangjie Chen, Tinghui Zhu, Kai Zhang, and Yanghua Xiao. 2024 · 2024
Closest in time.
Teilp: Time prediction over knowledge graphs via logical reasoning
Siheng Xiong, Yuan Yang, Ali Payani, James C Kerce, and Faramarz Fekri. 2024 · 2024
Closest in time.
Leveraging generative ai to prioritize drug repurposing candidates for alzheimer’s disease with real-world clinical validation
Chao Yan, Monika Grabowska, Alyson Dickson, Bingshan Li, Zhexing Wen, Dan Roden, C. Stein, Peter Embí, Josh Peterson, Qiping Feng, Bradley Malin, and Wei-Qi Wei. 2024 · 2024
Closest in time.
Self-rewarding language models
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Sainbayar Sukhbaatar, Jing Xu, and Jason Weston. 2024 · 2024
Closest in time.
Almanac—retrieval-augmented language models for clinical medicine
Cyril Zakka, Rohan Shad, Akash Chaurasia, Alex R Dalal, Jennifer L Kim, Michael Moor, Robyn Fong, Curran Phillips, Kevin Alexander, Euan Ashley, et al. 2024 · 2024
Closest in time.
Hengyuan Zhang, Yanru Wu, Dawei Li, Zacc Yang, Rui Zhao, Yong Jiang, and Fei Tan. 2024 · 2024
Closest in time.