1key,openalex_id,doi_or_arxiv,verified_via,verified_title,corpus_title,match,entry_type2bick2026rapidadoption,7124974472,doi:10.1287/mnsc.2025.02523,crossref,The Rapid Adoption of Generative AI,The Rapid Adoption of Generative AI,yes,journal-article3kasneci2023chatgptgood,4323655724,doi:10.1016/j.lindif.2023.102274,crossref,ChatGPT for good? On opportunities and challenges of large language models for education,ChatGPT for good? On opportunities and challenges of large language models for education,yes,journal-article4wang2019superglue,2990704537,arxiv:1905.00537,arxiv,SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems,SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems,yes,arxiv5han2024peftsurvey,4393138529,arxiv:2403.14608,arxiv,Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey,Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey,yes,arxiv6bodnar2025aurora,4410551352,doi:10.1038/s41586-025-09005-y,crossref,A foundation model for the Earth system,A foundation model for the Earth system,yes,journal-article7chen2024uni,4392947521,doi:10.1038/s41591-024-02857-3,crossref,Towards a general-purpose foundation model for computational pathology,Towards a general-purpose foundation model for computational pathology,yes,journal-article8wang2024chief,4402220065,doi:10.1038/s41586-024-07894-z,crossref,A pathology foundation model for cancer diagnosis and prognosis prediction,A pathology foundation model for cancer diagnosis and prognosis prediction,yes,journal-article9zhang2024biomedgpt,4401397240,doi:10.1038/s41591-024-03185-2,crossref,A generalist vision--language foundation model for diverse biomedical tasks,A generalist vision--language foundation model for diverse biomedical tasks,yes,journal-article10binz2025centaur,4411932262,doi:10.1038/s41586-025-09215-4,crossref,A foundation model to predict and capture human cognition,A foundation model to predict and capture human cognition,yes,journal-article11dai2023instructblip,7133220561,arxiv:2305.06500,arxiv,InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning,InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning,yes,arxiv12schuhmann2022laion5b,7133250524,arxiv:2210.08402,arxiv,LAION-5B: An open large-scale dataset for training next generation image-text models,LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models,yes,arxiv13su2019vlbert,2995460200,arxiv:1908.08530,arxiv,VL-BERT: Pre-training of Generic Visual-Linguistic Representations,VL-BERT: Pre-training of Generic Visual-Linguistic Representations,yes,arxiv14mou2024t2iadapter,4393148714,doi:10.1609/aaai.v38i5.28226,crossref,T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models,T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models,yes,journal-article15gal2022textualinversion,4289785095,arxiv:2208.01618,arxiv,An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion,An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion,yes,arxiv16buckley2026textexploit,7164501397,doi:10.1038/s41467-026-74207-5,crossref,Multimodal foundation models exploit text to make medical image predictions,Multimodal foundation models exploit text to make medical image predictions,yes,journal-article17zhang2026lowqualityfusion,4396599905,doi:10.1016/j.inffus.2026.104437,crossref,Multimodal fusion on low-quality data: A comprehensive survey,Multimodal fusion on low-quality data: A comprehensive survey,yes,journal-article18ho2022cfg,4288099666,arxiv:2207.12598,arxiv,Classifier-Free Diffusion Guidance,Classifier-Free Diffusion Guidance,yes,arxiv19zeni2025mattergen,4406472463,doi:10.1038/s41586-025-08628-5,crossref,A generative model for inorganic materials design,A generative model for inorganic materials design,yes,journal-article20bastani2024harmlearning,4400770292,doi:10.2139/ssrn.4895486,crossref,Generative AI Can Harm Learning,Generative AI Can Harm Learning,yes,posted-content21acharya2025agenticsurvey,4406728221,doi:10.1109/access.2025.3532853,crossref,Agentic AI: Autonomous Intelligence for Complex Goals---A Comprehensive Survey,Agentic AI: Autonomous Intelligence for Complex Goals---A Comprehensive Survey,yes,journal-article22ghareeb2026robin,7161734976,doi:10.1038/s41586-026-10652-y,crossref,A multi-agent system for automating scientific discovery,A multi-agent system for automating scientific discovery,yes,journal-article23swanson2025virtuallab,4412709685,doi:10.1038/s41586-025-09442-9,crossref,The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies,The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies,yes,journal-article24piao2026agentsociety,4407570917,doi:10.26599/if.2026.9710004,crossref,AgentSociety: Large-scale simulation of LLM-driven generative agents advances understanding of human behaviors and society,AgentSociety: Large-scale simulation of LLM-driven generative agents advances understanding of human behaviors and society,yes,journal-article25sapkota2026agentsvsagentic,4413427262,doi:10.1016/j.inffus.2025.103599,crossref,"AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges","AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges",yes,journal-article26zhang2025agentmemory,4412203333,doi:10.1145/3748302,crossref,A Survey on the Memory Mechanism of Large Language Model-based Agents,A Survey on the Memory Mechanism of Large Language Model-based Agents,yes,journal-article27liu2026clinicalagents,7130481397,doi:10.1038/s41746-026-02443-6,crossref,Benchmarking large language model-based agent systems for clinical decision tasks,Benchmarking large language model-based agent systems for clinical decision tasks,yes,journal-article28haarnoja2018sac,2781726626,arxiv:1801.01290,arxiv,Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,yes,arxiv29fujimoto2018td3,2963923407,arxiv:1802.09477,arxiv,Addressing Function Approximation Error in Actor-Critic Methods,Addressing Function Approximation Error in Actor-Critic Methods,yes,arxiv30vinyals2019alphastar,2982316857,doi:10.1038/s41586-019-1724-z,crossref,Grandmaster level in StarCraft II using multi-agent reinforcement learning,Grandmaster level in StarCraft II using multi-agent reinforcement learning,yes,journal-article31hessel2018rainbow,2761873684,doi:10.1609/aaai.v32i1.11796,crossref,Rainbow: Combining Improvements in Deep Reinforcement Learning,Rainbow: Combining Improvements in Deep Reinforcement Learning,yes,journal-article32yu2021mappo,7133226216,arxiv:2103.01955,arxiv,"The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games",The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games,yes,arxiv33hafner2025dreamerv3,4409147637,doi:10.1038/s41586-025-08744-2,crossref,Mastering diverse control tasks through world models,Mastering diverse control tasks through world models,yes,journal-article34burda2018curiosity,2964083594,arxiv:1808.04355,arxiv,Large-Scale Study of Curiosity-Driven Learning,Large-Scale Study of Curiosity-Driven Learning,yes,arxiv35zhang2021marloverview,2991046523,doi:10.1007/978-3-030-60990-0_12,crossref,Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms,Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms,yes,book-chapter36rudin2019stopexplaining,2945976633,doi:10.1038/s42256-019-0048-x,crossref,Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,yes,journal-article37lipton2018mythos,2439568532,doi:10.1145/3233231,crossref,The mythos of model interpretability,The Mythos of Model Interpretability,yes,journal-article38lundberg2020treeexplainer,2999615587,doi:10.1038/s42256-019-0138-9,crossref,From local explanations to global understanding with explainable AI for trees,From local explanations to global understanding with explainable AI for trees,yes,journal-article39chicco2020mcc,2999309192,doi:10.1186/s12864-019-6413-7,crossref,The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation,The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation,yes,journal-article40zhuang2021transfersurvey,3041133507,doi:10.1109/jproc.2020.3004555,crossref,A Comprehensive Survey on Transfer Learning,A Comprehensive Survey on Transfer Learning,yes,journal-article41bottou2018optimization,2436219157,doi:10.1137/16m1080173,crossref,Optimization Methods for Large-Scale Machine Learning,Optimization Methods for Large-Scale Machine Learning,yes,journal-article42zeng2023transformerstsf,4382203079,doi:10.1609/aaai.v37i9.26317,crossref,Are Transformers Effective for Time Series Forecasting?,Are Transformers Effective for Time Series Forecasting?,yes,journal-article43zhou2021informer,3177318507,doi:10.1609/aaai.v35i12.17325,crossref,Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting,Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting,yes,journal-article44wen2023tstransformers,4385763767,doi:10.24963/ijcai.2023/759,crossref,Transformers in Time Series: A Survey,Transformers in Time Series: A Survey,yes,proceedings-article45hollmann2025tabpfn,4406170795,doi:10.1038/s41586-024-08328-6,crossref,Accurate predictions on small data with a tabular foundation model,Accurate predictions on small data with a tabular foundation model,yes,journal-article46liu2024kan,4396821501,arxiv:2404.19756,arxiv,KAN: Kolmogorov-Arnold Networks,KAN: Kolmogorov-Arnold Networks,yes,arxiv47wu2021gnnsurvey,2907492528,doi:10.1109/tnnls.2020.2978386,crossref,A Comprehensive Survey on Graph Neural Networks,A Comprehensive Survey on Graph Neural Networks,yes,journal-article48zhou2020gnnreview,3152893301,doi:10.1016/j.aiopen.2021.01.001,crossref,Graph neural networks: A review of methods and applications,Graph neural networks: A review of methods and applications,yes,journal-article49zhang2017mixup,2963399829,arxiv:1710.09412,arxiv,mixup: Beyond Empirical Risk Minimization,Mixup: Beyond empirical risk minimization,yes,arxiv50barredoarrieta2020xai,2981731882,doi:10.1016/j.inffus.2019.12.012,crossref,"Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI","Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI",yes,journal-article51mehrabi2021biasfairness,2969896603,doi:10.1145/3457607,crossref,A Survey on Bias and Fairness in Machine Learning,A Survey on Bias and Fairness in Machine Learning,yes,journal-article52miller2019explanation,2670253439,doi:10.1016/j.artint.2018.07.007,crossref,Explanation in artificial intelligence: Insights from the social sciences,Explanation in artificial intelligence: Insights from the social sciences,yes,journal-article53ali2023xaitrust,4366262984,doi:10.1016/j.inffus.2023.101805,crossref,Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence,Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence,yes,journal-article54slattery2026riskrepository,4402698709,doi:10.1016/j.patter.2026.101517,crossref,"The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence","The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence",yes,journal-article55chao2025pair,4410609100,doi:10.1109/satml64287.2025.00010,crossref,Jailbreaking Black Box Large Language Models in Twenty Queries,Jailbreaking Black Box Large Language Models in Twenty Queries,yes,proceedings-article56alber2025poisoning,4406152291,doi:10.1038/s41591-024-03445-1,crossref,Medical large language models are vulnerable to data-poisoning attacks,Medical large language models are vulnerable to data-poisoning attacks,yes,journal-article57draelos2026unsafeanswers,7128782475,doi:10.1038/s41746-026-02428-5,crossref,Large language models provide unsafe answers to patient-posed medical questions,Large language models provide unsafe answers to patient-posed medical questions,yes,journal-article58moore2025stigma,4411542009,doi:10.1145/3715275.3732039,crossref,Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers.,Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers.,yes,proceedings-article59papagiannidis2025raigovernance,4406063062,doi:10.1016/j.jsis.2024.101885,crossref,Responsible artificial intelligence governance: A review and research framework,Responsible artificial intelligence governance: A review and research framework,yes,journal-article60mcdonald2025hepolicies,4406571986,doi:10.1016/j.chbah.2025.100121,crossref,Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines,Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines,yes,journal-article61lo2023rapidreview,4366420437,doi:10.3390/educsci13040410,crossref,What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature,What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature,yes,journal-article62chan2023students,4384464487,doi:10.1186/s41239-023-00411-8,crossref,"Students' voices on generative AI: perceptions, benefits, and challenges in higher education","Students' voices on generative AI: perceptions, benefits, and challenges in higher education",yes,journal-article63chan2023policyframework,4383312437,doi:10.1186/s41239-023-00408-3,crossref,A comprehensive AI policy education framework for university teaching and learning,A comprehensive AI policy education framework for university teaching and learning,yes,journal-article64baidooanu2023chatgptedu,4389437528,doi:10.61969/jai.1337500,crossref,Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning,Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning,yes,journal-article65rudolph2023assessment,4317910584,doi:10.37074/jalt.2023.6.1.9,crossref+openalex,ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?,ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?,yes,journal-article66lim2023ragnarok,4322617812,doi:10.1016/j.ijme.2023.100790,crossref,Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators,Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators,yes,journal-article67wu2025radfm,4413447271,doi:10.1038/s41467-025-62385-7,crossref,Towards generalist foundation model for radiology by leveraging web-scale 2D\&3D medical data,Towards generalist foundation model for radiology by leveraging web-scale 2D\&3D medical data,yes,journal-article68ding2025titan,4415913530,doi:10.1038/s41591-025-03982-3,crossref,A multimodal whole-slide foundation model for pathology,A multimodal whole-slide foundation model for pathology,yes,journal-article69lu2024conch,4392947532,doi:10.1038/s41591-024-02856-4,crossref,A visual-language foundation model for computational pathology,A visual-language foundation model for computational pathology,yes,journal-article70huang2023plip,4385948838,doi:10.1038/s41591-023-02504-3,crossref,A visual--language foundation model for pathology image analysis using medical Twitter,A visual--language foundation model for pathology image analysis using medical Twitter,yes,journal-article71yan2025panderm,4411099958,doi:10.1038/s41591-025-03747-y,crossref,A multimodal vision foundation model for clinical dermatology,A multimodal vision foundation model for clinical dermatology,yes,journal-article72tak2026brainiac,7128029160,doi:10.1038/s41593-026-02202-6,crossref,A generalizable foundation model for analysis of human brain MRI,A generalizable foundation model for analysis of human brain MRI,yes,journal-article73zhu2026earthfm,7119541039,doi:10.1038/s43247-025-03127-x,crossref,On the foundations of Earth foundation models,On the foundations of Earth foundation models,yes,journal-article74singhal2023clinical,4384071683,doi:10.1038/s41586-023-06291-2,crossref,Large language models encode clinical knowledge,Large language models encode clinical knowledge,yes,journal-article75liu2023prompting,3185341429,doi:10.1145/3560815,crossref,"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing",yes,journal-article76vandis2023priorities,4319083882,doi:10.1038/d41586-023-00288-7,crossref,ChatGPT: five priorities for research,ChatGPT: five priorities for research,yes,journal-article77cheng2026agentsdefinitions,4390730779,doi:10.1002/widm.70111,crossref,"Exploring Large Language Model-Based Intelligent Agents: Definitions, Methods, and Prospects","Exploring Large Language Model-Based Intelligent Agents: Definitions, Methods, and Prospects",yes,journal-article78raza2026trism,7133236347,doi:10.1016/j.aiopen.2026.02.006,crossref,"TRiSM for Agentic AI: A review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems","TRiSM for Agentic AI: A review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems",yes,journal-article79paschali2025fmradiology,4407135816,doi:10.1148/radiol.240597,crossref,"Foundation Models in Radiology: What, How, Why, and Why Not","Foundation Models in Radiology: What, How, Why, and Why Not",yes,journal-article80zhang2026datacentric,4390690043,doi:10.1145/3800677,crossref,Data-Centric Foundation Models in Computational Healthcare: A Survey,Data-Centric Foundation Models in Computational Healthcare: A Survey,yes,journal-article81zheng2025learningfrommodels,4406472599,doi:10.1038/s42256-024-00961-0,crossref,Learning from models beyond fine-tuning,Learning from models beyond fine-tuning,yes,journal-article82schouten2025multimodalmedicine,4410882873,doi:10.1016/j.media.2025.103621,crossref,Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications,Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications,yes,journal-article83zhai2024overreliance,4399790131,doi:10.1186/s40561-024-00316-7,crossref,The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review,The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review,yes,journal-article84xia2024assessmentreview,4398243313,doi:10.1186/s41239-024-00468-z,crossref,A scoping review on how generative artificial intelligence transforms assessment in higher education,A scoping review on how generative artificial intelligence transforms assessment in higher education,yes,journal-article85bittle2025integrity,4409269614,doi:10.3390/info16040296,crossref,Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda,Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda,yes,journal-article86jin2023timellm,4387355843,arxiv:2310.01728,arxiv,Time-LLM: Time Series Forecasting by Reprogramming Large Language Models,TimeLLM: Time Series Forecasting by Reprogramming Large Language Models,yes,arxiv87liu2024timesurl,4393153153,doi:10.1609/aaai.v38i12.29299,crossref,TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning,TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning,yes,journal-article88ye2024mplugowl2,4402727669,doi:10.1109/cvpr52733.2024.01239,crossref,mPLUG-OwI2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration,mPLUG-OwI2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration,yes,proceedings-article89wang2025gpt5medical,7148475777,arxiv:2508.08224,arxiv,Capabilities of GPT-5 on Multimodal Medical Reasoning,Capabilities of GPT-5 on multimodal medical reasoning,yes,arxiv90lai2026medr1,7127319731,doi:10.1109/tmi.2026.3661001,crossref,Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models,Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models,yes,journal-article91zhang2026dive,4414991289,doi:10.1039/d5sc09921h,crossref,``DIVE'' into hydrogen storage materials discovery with AI agents,``DIVE'' into hydrogen storage materials discovery with AI agents,yes,journal-article92bandi2025agenticreview,4414023998,doi:10.3390/fi17090404,crossref,"The Rise of Agentic AI: A Review of Definitions, Frameworks, Architectures, Applications, Evaluation Metrics, and Challenges","The Rise of Agentic AI: A Review of Definitions, Frameworks, Architectures, Applications, Evaluation Metrics, and Challenges",yes,journal-article93abouali2025agenticparadigms,4416209823,doi:10.1007/s10462-025-11422-4,crossref,"Agentic AI: a comprehensive survey of architectures, applications, and future directions","Agentic AI: a comprehensive survey of architectures, applications, and future directions",yes,journal-article94allmendinger2026multiagentai,7128165235,doi:10.1007/s12525-025-00862-z,crossref,Multi-agent AI,Multi-agent AI,yes,journal-article95hasanzadeh2025biashealthcare,4408314709,doi:10.1038/s41746-025-01503-7,crossref,Bias recognition and mitigation strategies in artificial intelligence healthcare applications,Bias recognition and mitigation strategies in artificial intelligence healthcare applications,yes,journal-article96wang2026pedagogical,7140170686,doi:10.1186/s41239-026-00585-x,crossref,Pedagogical partnerships with generative AI in higher education: how dual cognitive pathways paradoxically enable transformative learning,Pedagogical partnerships with generative AI in higher education: how dual cognitive pathways paradoxically enable transformative learning,yes,journal-article97collaco2026agentichealthcare,7135409568,doi:10.1038/s41746-026-02517-5,crossref,The role of agentic artificial intelligence in healthcare: a scoping review,The role of agentic artificial intelligence in healthcare: a scoping review,yes,journal-article98gholami2022quantization,3137147200,doi:10.1201/9781003162810-13,crossref,A Survey of Quantization Methods for Efficient Neural Network Inference,A Survey of Quantization Methods for Efficient Neural Network Inference,yes,book-chapter99zhang2023llamaadapter,4361229539,arxiv:2303.16199,arxiv,LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention,LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention,yes,arxiv100