Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have demonstrated remarkable capabilities in many real-world applications.
The Unified Medical Language System (UMLS): integrating biomedical terminology
Olivier Bodenreider · 2004
Earlier work this paper cites.
Exploring compact reinforcement-learning representations with linear regression
Thomas J Walsh, István Szita, Carlos Diuk, and Michael L Littman · 2009
Earlier work this paper cites.
Meta-learning with memory-augmented neural networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap · 2016
Earlier work this paper cites.
Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi · 2017
Earlier work this paper cites.
DrugBank 5.0: a major update to the DrugBank database for 2018
David S Wishart, Yannick D Feunang, An C Guo, Elvis J Lo, Ana Marcu, Jason R Grant, Tanvir Sajed, Daniel Johnson, Carin Li, Zinat Sayeeda, Nazanin Assempour, Ithayavani Iynkkaran, Yifeng Liu, Adam Maciejewski, Nicola Gale, Alex Wilson, Lucy Chin, Ryan Cummings, Diana Le, Allison Pon, Craig Knox, and Michael Wilson · 2017
Earlier work this paper cites.
Deeppath: A reinforcement learning method for knowledge graph reasoning
Wenhan Xiong, Thien Hoang, and William Yang Wang · 2017
Earlier work this paper cites.
Clipped action policy gradient
Yasuhiro Fujita and Shin-ichi Maeda · 2018
Earlier work this paper cites.
Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal · 2018
Earlier work this paper cites.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
Earlier work this paper cites.
Publicly available clinical bert embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott · 2019
Earlier work this paper cites.
Neural legal judgment prediction in english
Ilias Chalkidis, Ion Androutsopoulos, and Nikolaos Aletras · 2019
Earlier work this paper cites.
A new algorithm for non-stationary contextual bandits: Efficient, optimal and parameter-free
Yifang Chen, Chung-Wei Lee, Haipeng Luo, and Chen-Yu Wei · 2019
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
Earlier work this paper cites.
Kagnet: Knowledge-aware graph networks for commonsense reasoning
Bill Yuchen Lin, Xinyue Chen, Jamin Chen, and Xiang Ren · 2019
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Earlier work this paper cites.
Knowledge enhanced contextual word representations
Matthew E Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A Smith · 2019
Earlier work this paper cites.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
From ‘f’to ‘a’on the ny regents science exams: An overview of the aristo project
Peter Clark, Oren Etzioni, Tushar Khot, Daniel Khashabi, Bhavana Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, et al · 2020
Earlier work this paper cites.
Scalable multi-hop relational reasoning for knowledge-aware question answering
Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, Peifeng Wang, Jun Yan, and Xiang Ren · 2020
Earlier work this paper cites.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A Smith · 2020
Earlier work this paper cites.
Unifiedqa: Crossing format boundaries with a single qa system
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi · 2020
Earlier work this paper cites.
Patent classification by fine-tuning bert language model
Jieh-Sheng Lee and Jieh Hsiang · 2020
Earlier work this paper cites.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
Earlier work this paper cites.
K-bert: Enabling language representation with knowledge graph
Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, and Ping Wang · 2020
Earlier work this paper cites.
How does nlp benefit legal system: A summary of legal artificial intelligence
Haoxi Zhong, Chaojun Xiao, Cunchao Tu, Tianyang Zhang, Zhiyuan Liu, and Maosong Sun · 2020
Cited alongside, same era.
Lexglue: A benchmark dataset for legal language understanding in english
Ilias Chalkidis, Abhik Jana, Dirk Hartung, Michael Bommarito, Ion Androutsopoulos, Daniel Martin Katz, and Nikolaos Aletras · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Self-alignment pretraining for biomedical entity representations
Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, and Nigel Collier · 2021
Cited alongside, same era.
Rethinking search: making domain experts out of dilettantes
Donald Metzler, Yi Tay, Dara Bahri, and Marc Najork · 2021
Cited alongside, same era.
Active ensemble learning for knowledge graph error detection
Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, and Zhao Zihao · 2023
Closest in time.
Learning to fake it: limited responses and fabricated references provided by chatgpt for medical questions
Jocelyn Gravel, Madeleine D’Amours-Gravel, and Esli Osmanlliu · 2023
Closest in time.
A survey of knowledge enhanced pre-trained language models
Linmei Hu, Zeyi Liu, Ziwang Zhao, Lei Hou, Liqiang Nie, and Juanzi Li · 2023
Closest in time.
Mvp-tuning: Multi-view knowledge retrieval with prompt tuning for commonsense reasoning
Yongfeng Huang, Yanyang Li, Yichong Xu, Lin Zhang, Ruyi Gan, Jiaxing Zhang, and Liwei Wang · 2023
Closest in time.
Performance of chatgpt on usmle: Potential for ai-assisted medical education using large language models
Tiffany H Kung, Morgan Cheatham, Arielle Medenilla, Czarina Sillos, Lorie De Leon, Camille Elepaño, Maria Madriaga, Rimel Aggabao, Giezel Diaz-Candido, James Maningo, et al · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ernie 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation
Yu Sun, Shuohuan Wang, Shikun Feng, Siyu Ding, Chao Pang, Junyuan Shang, Jiaxiang Liu, Xuyi Chen, Yanbin Zhao, Yuxiang Lu, et al · 2021
Cited alongside, same era.
Gnn is a counter? revisiting gnn for question answering, 2021
Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, and Tao Qin · 2021
Cited alongside, same era.
Kepler: A unified model for knowledge embedding and pre-trained language representation
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhengyan Zhang, Zhiyuan Liu, Juanzi Li, and Jian Tang · 2021
Cited alongside, same era.
Qa-gnn: Reasoning with language models and knowledge graphs for question answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec · 2021
Cited alongside, same era.
Retrieving and reading: A comprehensive survey on open-domain question answering
Fengbin Zhu, Wenqiang Lei, Chao Wang, Jianming Zheng, Soujanya Poria, and Tat-Seng Chua · 2021
Cited alongside, same era.
Glm: General language model pretraining with autoregressive blank infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang · 2022
Cited alongside, same era.
Clues before answers: Generation-enhanced multiple-choice qa
Zixian Huang, Ao Wu, Jiaying Zhou, Yu Gu, Yue Zhao, and Gong Cheng · 2022
Cited alongside, same era.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
Closest in time.
Reasoning on graphs: Faithful and interpretable large language model reasoning
Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, and Shirui Pan · 2023
Closest in time.
Gpt-4 technical report, 2023
OpenAI · 2023
Closest in time.
In chatgpt we trust? measuring and characterizing the reliability of chatgpt
Xinyue Shen, Zeyuan Chen, Michael Backes, and Yang Zhang · 2023
Closest in time.
Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering
Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Tharindu Kaluarachchi, Rajib Rana, and Suranga Nanayakkara · 2023
Closest in time.
Grapeqa: Graph augmentation and pruning to enhance question-answering
Dhaval Taunk, Lakshya Khanna, Siri Venkata Pavan Kumar Kandru, Vasudeva Varma, Charu Sharma, and Makarand Tapaswi · 2023
Closest in time.
Internlm: A multilingual language model with progressively enhanced capabilities, 2023
InternLM Team · 2023
Closest in time.
Boosting language models reasoning with chain-of-knowledge prompting
Jianing Wang, Qiushi Sun, Nuo Chen, Xiang Li, and Ming Gao · 2023
Closest in time.
Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models
Yilin Wen, Zifeng Wang, and Jimeng Sun · 2023
Closest in time.
Data-centric artificial intelligence: A survey
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, and Xia Hu · 2023
Closest in time.
Integrating entity attributes for error-aware knowledge graph embedding
Qinggang Zhang, Junnan Dong, Qiaoyu Tan, and Xiao Huang · 2023
Closest in time.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
Closest in time.
The claude 3 model family: Opus, sonnet, haiku
AI Anthropic · 2024
Closest in time.
Openagi: When llm meets domain experts
Yingqiang Ge, Wenyue Hua, Kai Mei, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang, et al · 2024
Closest in time.
Does fine-tuning llms on new knowledge encourage hallucinations?
Zorik Gekhman, Gal Yona, Roee Aharoni, Matan Eyal, Amir Feder, Roi Reichart, and Jonathan Herzig · 2024
Closest in time.
Mitigating large language model hallucinations via autonomous knowledge graph-based retrofitting
Xinyan Guan, Yanjiang Liu, Hongyu Lin, Yaojie Lu, Ben He, Xianpei Han, and Le Sun · 2024
Closest in time.
Large language models: A survey
Shervin Minaee, Tomas Mikolov, Narjes Nikzad, Meysam Chenaghlu, Richard Socher, Xavier Amatriain, and Jianfeng Gao · 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
Closest in time.
Differentiable neuro-symbolic reasoning on large-scale knowledge graphs
Chen Shengyuan, Yunfeng Cai, Huang Fang, Xiao Huang, and Mingming Sun · 2024
Closest in time.
Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling
Linyao Yang, Hongyang Chen, Zhao Li, Xiao Ding, and Xindong Wu · 2024
Closest in time.
Self-distillation bridges distribution gap in language model fine-tuning
Zhaorui Yang, Qian Liu, Tianyu Pang, Han Wang, Haozhe Feng, Minfeng Zhu, and Wei Chen · 2024
Closest in time.