key,doi_or_arxiv,verified_via,verified_title,match,note
priem2022openalex,arXiv:2205.01833,arxiv,"OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts",exact,
kinney2023s2,arXiv:2301.10140,arxiv,The Semantic Scholar Open Data Platform,exact,
culbert2024openalex,arXiv:2401.16359,arxiv,Reference Coverage Analysis of OpenAlex compared to Web of Science and Scopus,exact,key renamed from culbert2025openalex to match year of record
sutskever2014seq2seq,arXiv:1409.3215,arxiv,Sequence to Sequence Learning with Neural Networks,exact,
bahdanau2014attention,arXiv:1409.0473,arxiv,Neural Machine Translation by Jointly Learning to Align and Translate,exact,key renamed from bahdanau2015attention to match year of record
goodfellow2014gan,arXiv:1406.2661,arxiv,Generative Adversarial Networks,exact,
mikolov2013word2vec,arXiv:1301.3781,arxiv,Efficient Estimation of Word Representations in Vector Space,exact,
kingma2013vae,arXiv:1312.6114,arxiv,Auto-Encoding Variational Bayes,exact,key renamed from kingma2014vae to match year of record
sevilla2022compute,arXiv:2202.05924,arxiv,Compute Trends Across Three Eras of Machine Learning,exact,
thompson2020limits,arXiv:2007.05558,arxiv,The Computational Limits of Deep Learning,exact,
ahmed2020dedemocratization,arXiv:2010.15581,arxiv,The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research,exact,
abadi2016tensorflow,arXiv:1605.08695,arxiv,TensorFlow: A system for large-scale machine learning,exact,
paszke2019pytorch,arXiv:1912.01703,arxiv,"PyTorch: An Imperative Style, High-Performance Deep Learning Library",exact,
vaswani2017attention,arXiv:1706.03762,arxiv,Attention Is All You Need,exact,
brown2020gpt3,arXiv:2005.14165,arxiv,Language Models are Few-Shot Learners,exact,
raffel2019t5,arXiv:1910.10683,arxiv,Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer,exact,key renamed from raffel2020t5 to match year of record
kaplan2020scaling,arXiv:2001.08361,arxiv,Scaling Laws for Neural Language Models,exact,
hoffmann2022chinchilla,arXiv:2203.15556,arxiv,Training Compute-Optimal Large Language Models,exact,
chowdhery2022palm,arXiv:2204.02311,arxiv,PaLM: Scaling Language Modeling with Pathways,exact,
fedus2021switch,arXiv:2101.03961,arxiv,Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity,exact,key renamed from fedus2022switch to match year of record
dosovitskiy2020vit,arXiv:2010.11929,arxiv,An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,exact,key renamed from dosovitskiy2021vit to match year of record
radford2021clip,arXiv:2103.00020,arxiv,Learning Transferable Visual Models From Natural Language Supervision,exact,
ramesh2021dalle,arXiv:2102.12092,arxiv,Zero-Shot Text-to-Image Generation,exact,
ho2020ddpm,arXiv:2006.11239,arxiv,Denoising Diffusion Probabilistic Models,exact,
sohl2015diffusion,arXiv:1503.03585,arxiv,Deep Unsupervised Learning using Nonequilibrium Thermodynamics,exact,
song2020score,arXiv:2011.13456,arxiv,Score-Based Generative Modeling through Stochastic Differential Equations,exact,key renamed from song2021score to match year of record
dhariwal2021beats,arXiv:2105.05233,arxiv,Diffusion Models Beat GANs on Image Synthesis,exact,
bommasani2021foundation,arXiv:2108.07258,arxiv,On the Opportunities and Risks of Foundation Models,exact,
wei2022cot,arXiv:2201.11903,arxiv,Chain-of-Thought Prompting Elicits Reasoning in Large Language Models,exact,
wei2022emergent,arXiv:2206.07682,arxiv,Emergent Abilities of Large Language Models,exact,
chen2021codex,arXiv:2107.03374,arxiv,Evaluating Large Language Models Trained on Code,exact,
ouyang2022instructgpt,arXiv:2203.02155,arxiv,Training language models to follow instructions with human feedback,exact,
christiano2017rlhf,arXiv:1706.03741,arxiv,Deep reinforcement learning from human preferences,exact,
stiennon2020summarize,arXiv:2009.01325,arxiv,Learning to summarize from human feedback,exact,
bai2022hh,arXiv:2204.05862,arxiv,Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback,exact,
lewis2020rag,arXiv:2005.11401,arxiv,Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,exact,
hendrycks2020mmlu,arXiv:2009.03300,arxiv,Measuring Massive Multitask Language Understanding,exact,key renamed from hendrycks2021mmlu to match year of record
wang2019superglue,arXiv:1905.00537,arxiv,SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems,exact,
srivastava2022bigbench,arXiv:2206.04615,arxiv,Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models,exact,key renamed from srivastava2023bigbench to match year of record
patterson2021carbon,arXiv:2104.10350,arxiv,Carbon Emissions and Large Neural Network Training,exact,
shoeybi2019megatron,arXiv:1909.08053,arxiv,Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism,exact,
rajbhandari2019zero,arXiv:1910.02054,arxiv,ZeRO: Memory Optimizations Toward Training Trillion Parameter Models,exact,key renamed from rajbhandari2020zero to match year of record
dao2022flashattention,arXiv:2205.14135,arxiv,FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness,exact,
rae2021gopher,arXiv:2112.11446,arxiv,"Scaling Language Models: Methods, Analysis & Insights from Training Gopher",exact,
bigscience2022bloom,arXiv:2211.05100,arxiv,BLOOM: A 176B-Parameter Open-Access Multilingual Language Model,exact,key scao2022bloom renamed bigscience2022bloom (first author / publication year)
zhang2022opt,arXiv:2205.01068,arxiv,OPT: Open Pre-trained Transformer Language Models,exact,
liu2019roberta,arXiv:1907.11692,arxiv,RoBERTa: A Robustly Optimized BERT Pretraining Approach,exact,
chen2020simclr,arXiv:2002.05709,arxiv,A Simple Framework for Contrastive Learning of Visual Representations,exact,
baevski2020wav2vec,arXiv:2006.11477,arxiv,wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations,exact,
alayrac2022flamingo,arXiv:2204.14198,arxiv,Flamingo: a Visual Language Model for Few-Shot Learning,exact,
reed2022gato,arXiv:2205.06175,arxiv,A Generalist Agent,exact,
saharia2022imagen,arXiv:2205.11487,arxiv,Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding,exact,
ramesh2022dalle2,arXiv:2204.06125,arxiv,Hierarchical Text-Conditional Image Generation with CLIP Latents,exact,
jonas2019serverless,arXiv:1902.03383,arxiv,Cloud Programming Simplified: A Berkeley View on Serverless Computing,exact,
hellerstein2018serverless,arXiv:1812.03651,arxiv,"Serverless Computing: One Step Forward, Two Steps Back",exact,key renamed from hellerstein2019serverless to match year of record
chen2018tvm,arXiv:1802.04799,arxiv,TVM: An Automated End-to-End Optimizing Compiler for Deep Learning,exact,
jacot2018ntk,arXiv:1806.07572,arxiv,Neural Tangent Kernel: Convergence and Generalization in Neural Networks,exact,
lu2021codexglue,arXiv:2102.04664,arxiv,CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation,exact,
szegedy2013intriguing,arXiv:1312.6199,arxiv,Intriguing properties of neural networks,exact,key renamed from szegedy2014intriguing to match year of record
mcmahan2016fl,arXiv:1602.05629,arxiv,Communication-Efficient Learning of Deep Networks from Decentralized Data,exact,key renamed from mcmahan2017fl to match year of record
li2020fno,arXiv:2010.08895,arxiv,Fourier Neural Operator for Parametric Partial Differential Equations,exact,key renamed from li2021fno to match year of record
luccioni2022bloom,arXiv:2211.02001,arxiv,"Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model",exact,key renamed from luccioni2023bloom to match year of record
levine2015visuomotor,arXiv:1504.00702,arxiv,End-to-End Training of Deep Visuomotor Policies,exact,key renamed from levine2016visuomotor to match year of record
openai2023gpt4,arXiv:2303.08774,arxiv,GPT-4 Technical Report,exact,
touvron2023llama,arXiv:2302.13971,arxiv,LLaMA: Open and Efficient Foundation Language Models,exact,
touvron2023llama2,arXiv:2307.09288,arxiv,Llama 2: Open Foundation and Fine-Tuned Chat Models,exact,
grattafiori2024llama3,arXiv:2407.21783,arxiv,The Llama 3 Herd of Models,exact,key dubey2024llama3 renamed grattafiori2024llama3 (first author / publication year)
bubeck2023sparks,arXiv:2303.12712,arxiv,Sparks of Artificial General Intelligence: Early experiments with GPT-4,exact,
openai2024o1,arXiv:2412.16720,arxiv,OpenAI o1 System Card,exact,
deepseek2025r1,arXiv:2501.12948,arxiv,DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning,exact,
gu2023mamba,arXiv:2312.00752,arxiv,Mamba: Linear-Time Sequence Modeling with Selective State Spaces,exact,
yao2022react,arXiv:2210.03629,arxiv,ReAct: Synergizing Reasoning and Acting in Language Models,exact,key renamed from yao2023react to match year of record
schick2023toolformer,arXiv:2302.04761,arxiv,Toolformer: Language Models Can Teach Themselves to Use Tools,exact,
gemini2023,arXiv:2312.11805,arxiv,Gemini: A Family of Highly Capable Multimodal Models,exact,
radford2022whisper,arXiv:2212.04356,arxiv,Robust Speech Recognition via Large-Scale Weak Supervision,exact,key renamed from radford2023whisper to match year of record
brohan2023rt2,arXiv:2307.15818,arxiv,RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control,exact,
liang2024monitoring,arXiv:2403.07183,arxiv,Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews,exact,
liang2024mapping,arXiv:2404.01268,arxiv,Mapping the Increasing Use of LLMs in Scientific Papers,exact,
geng2024writing,arXiv:2404.08627,arxiv,Is ChatGPT Transforming Academics' Writing Style?,exact,
gray2024contamination,arXiv:2403.16887,arxiv,"ChatGPT ""contamination"": estimating the prevalence of LLMs in the scholarly literature",exact,
ott2022benchmarks,arXiv:2203.04592,arxiv,Mapping global dynamics of benchmark creation and saturation in artificial intelligence,exact,
dehghani2021lottery,arXiv:2107.07002,arxiv,The Benchmark Lottery,exact,
raji2021benchmark,arXiv:2111.15366,arxiv,AI and the Everything in the Whole Wide World Benchmark,exact,
maslej2024aiindex,arXiv:2405.19522,arxiv,Artificial Intelligence Index Report 2024,exact,
maslej2025aiindex,arXiv:2504.07139,arxiv,Artificial Intelligence Index Report 2025,exact,
pineau2020reproducibility,arXiv:2003.12206,arxiv,Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program),exact,key renamed from pineau2021reproducibility to match year of record
hendrycks2021unsolved,arXiv:2109.13916,arxiv,Unsolved Problems in ML Safety,exact,
liang2025widespread,arXiv:2502.09747,arxiv,The Widespread Adoption of Large Language Model-Assisted Writing Across Society,exact,"key renamed: first author is Liang, not Kobak"
ley2002dblp,10.1007/3-540-45735-6_1,crossref,"The DBLP Computer Science Bibliography: Evolution, Research Issues, Perspectives",exact,
ginsparg2011arxiv,10.1038/476145a,crossref,ArXiv at 20,exact,
wang2020mag,10.1162/qss_a_00021,crossref,Microsoft Academic Graph: When experts are not enough,exact,
waltman2012classification,10.1002/asi.22748,crossref,A new methodology for constructing a publication‐level classification system of science,exact,
glanzel2003classification,10.1023/A:1022378804087,crossref,A new classification scheme of science fields and subfields designed for scientometric evaluation purposes,exact,
klavans2017taxonomy,10.1002/asi.23734,crossref,Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?,exact,
sjogarde2018granularity,10.1016/j.joi.2017.12.006,crossref,Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics,exact,
traag2019leiden,10.1038/s41598-019-41695-z,crossref,From Louvain to Leiden: guaranteeing well-connected communities,exact,
rous2012ccs,10.1145/2366316.2366320,crossref,Major update to ACM's Computing Classification System,exact,
vardi2009conferences,10.1145/1506409.1506410,crossref,Conferences vs. journals in computing research,exact,
fortnow2009growup,10.1145/1536616.1536631,crossref,ViewpointTime for computer science to grow up,minor,Crossref title concatenates 'Viewpoint' label; record matches
lin2020preprints,10.1007/s11192-020-03430-8,crossref,How many preprints have actually been printed and why: a case study of computer science preprints on arXiv,exact,
denning2005science,10.1145/1053291.1053309,crossref,Is computer science science?,exact,
wing2006computational,10.1145/1118178.1118215,crossref,Computational thinking,exact,
bornmann2021growth,10.1057/s41599-021-00903-w,crossref,Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases,exact,
visser2021comparison,10.1162/qss_a_00112,crossref,"Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic",exact,
martinmartin2021coverage,10.1007/s11192-020-03690-4,crossref,"Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations",exact,
bernerslee1994www,10.1145/179606.179671,crossref,The World-Wide Web,exact,
brin1998anatomy,10.1016/S0169-7552(98)00110-X,crossref,The anatomy of a large-scale hypertextual Web search engine,exact,
dean2008mapreduce,10.1145/1327452.1327492,crossref,MapReduce: simplified data processing on large clusters,exact,title+subtitle fields
armbrust2010cloud,10.1145/1721654.1721672,crossref,A view of cloud computing,exact,
ghemawat2003gfs,10.1145/945445.945450,crossref,The Google file system,exact,
kleinberg1999hubs,10.1145/324133.324140,crossref,Authoritative sources in a hyperlinked environment,exact,
krizhevsky2017imagenet,10.1145/3065386,crossref,ImageNet classification with deep convolutional neural networks,exact,
deng2009imagenet,10.1109/CVPR.2009.5206848,crossref,ImageNet: A large-scale hierarchical image database,exact,
russakovsky2015imagenet,10.1007/s11263-015-0816-y,crossref,ImageNet Large Scale Visual Recognition Challenge,exact,
he2016resnet,10.1109/CVPR.2016.90,crossref,Deep Residual Learning for Image Recognition,exact,
lecun2015deep,10.1038/nature14539,crossref,Deep learning,exact,
silver2016alphago,10.1038/nature16961,crossref,Mastering the game of Go with deep neural networks and tree search,exact,
silver2017alphagozero,10.1038/nature24270,crossref,Mastering the game of Go without human knowledge,exact,
silver2018alphazero,10.1126/science.aar6404,crossref,"A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play",exact,
mnih2015dqn,10.1038/nature14236,crossref,Human-level control through deep reinforcement learning,exact,
hochreiter1997lstm,10.1162/neco.1997.9.8.1735,crossref,Long Short-Term Memory,exact,
hinton2012speech,10.1109/MSP.2012.2205597,crossref,Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups,exact,title+subtitle fields
lipton2019troubling,10.1145/3317287.3328534,crossref,Troubling Trends in Machine Learning Scholarship,exact,
ahmed2023industry,10.1126/science.ade2420,crossref,The growing influence of industry in AI research,exact,
wolf2020transformers,10.18653/v1/2020.emnlp-demos.6,crossref,Transformers: State-of-the-Art Natural Language Processing,exact,
vinyals2019alphastar,10.1038/s41586-019-1724-z,crossref,Grandmaster level in StarCraft II using multi-agent reinforcement learning,exact,
devlin2019bert,10.18653/v1/N19-1423,crossref,BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,exact,
peters2018elmo,10.18653/v1/N18-1202,crossref,Deep Contextualized Word Representations,exact,
rombach2022ldm,10.1109/CVPR52688.2022.01042,crossref,High-Resolution Image Synthesis with Latent Diffusion Models,exact,
jumper2021alphafold,10.1038/s41586-021-03819-2,crossref,Highly accurate protein structure prediction with AlphaFold,exact,
bender2021parrots,10.1145/3442188.3445922,crossref,On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?,exact,title+subtitle fields (Crossref title ends with a parrot emoji)
wang2018glue,10.18653/v1/W18-5446,crossref,GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding,exact,
rajpurkar2016squad,10.18653/v1/D16-1264,crossref,"SQuAD: 100,000+ Questions for Machine Comprehension of Text",exact,
strubell2019energy,10.18653/v1/P19-1355,crossref,Energy and Policy Considerations for Deep Learning in NLP,exact,
schwartz2020green,10.1145/3381831,crossref,Green AI,exact,
he2022mae,10.1109/CVPR52688.2022.01553,crossref,Masked Autoencoders Are Scalable Vision Learners,exact,
caron2021dino,10.1109/ICCV48922.2021.00951,crossref,Emerging Properties in Self-Supervised Vision Transformers,exact,
dean2013tail,10.1145/2408776.2408794,crossref,The tail at scale,exact,
barroso2018datacenter,10.2200/S00874ED3V01Y201809CAC046,openalex,"The Datacenter as a Computer: Designing Warehouse-Scale Machines, Third Edition",exact,crossref timed out; verified via OpenAlex
lim2009disaggregated,10.1145/1555754.1555789,crossref,Disaggregated memory for expansion and sharing in blade servers,exact,
zaharia2016spark,10.1145/2934664,crossref,Apache Spark: a unified engine for big data processing,exact,title+subtitle fields
hennessy2019golden,10.1145/3282307,crossref,A new golden age for computer architecture,exact,
esmaeilzadeh2011dark,10.1145/2000064.2000108,crossref,Dark silicon and the end of multicore scaling,exact,
jouppi2017tpu,10.1145/3079856.3080246,crossref,In-Datacenter Performance Analysis of a Tensor Processing Unit,exact,
leiserson2020room,10.1126/science.aam9744,crossref,There’s plenty of room at the Top: What will drive computer performance after Moore’s law?,exact,
dennard1974scaling,10.1109/JSSC.1974.1050511,crossref,Design of ion-implanted MOSFET's with very small physical dimensions,exact,
lattner2021mlir,10.1109/CGO51591.2021.9370308,crossref,MLIR: Scaling Compiler Infrastructure for Domain Specific Computation,exact,
williams2019finegrained,10.1142/9789813272880_0188,crossref,ON SOME FINE-GRAINED QUESTIONS IN ALGORITHMS AND COMPLEXITY,exact,key renamed from williams2018finegrained to match year of record
vassilevska2015hardness,10.4230/LIPIcs.IPEC.2015.17,openalex,Hardness of Easy Problems: Basing Hardness on Popular Conjectures such as the Strong Exponential Time Hypothesis (Invited Talk),minor,OpenAlex title adds '(Invited Talk)'
zhang2021rethinking,10.1145/3446776,crossref,Understanding deep learning (still) requires rethinking generalization,exact,
belkin2019reconciling,10.1073/pnas.1903070116,crossref,Reconciling modern machine-learning practice and the classical bias–variance trade-off,exact,
preskill2018nisq,10.22331/q-2018-08-06-79,crossref,Quantum Computing in the NISQ era and beyond,exact,
arute2019supremacy,10.1038/s41586-019-1666-5,crossref,Quantum supremacy using a programmable superconducting processor,exact,
bharti2022nisq,10.1103/RevModPhys.94.015004,crossref,Noisy intermediate-scale quantum algorithms,exact,
google2023surface,10.1038/s41586-022-05434-1,crossref,Suppressing quantum errors by scaling a surface code logical qubit,exact,
google2025threshold,10.1038/s41586-024-08449-y,crossref,Quantum error correction below the surface code threshold,exact,key google2024threshold renamed google2025threshold (first author / publication year)
jung2018rustbelt,10.1145/3158154,crossref,RustBelt: securing the foundations of the Rust programming language,exact,key renamed from jung2017rustbelt to match year of record
matsakis2014rust,10.1145/2692956.2663188,crossref,The rust language,exact,
leroy2009compcert,10.1145/1538788.1538814,crossref,Formal verification of a realistic compiler,exact,
klein2009sel4,10.1145/1629575.1629596,crossref,seL4: formal verification of an OS kernel,exact,title+subtitle fields
demoura2015lean,10.1007/978-3-319-21401-6_26,crossref,The Lean Theorem Prover (System Description),exact,
demoura2021lean4,10.1007/978-3-030-79876-5_37,crossref,The Lean 4 Theorem Prover and Programming Language,exact,
mathlib2020,10.1145/3372885.3373824,crossref,The lean mathematical library,exact,
hales2017kepler,10.1017/fmp.2017.1,crossref,A FORMAL PROOF OF THE KEPLER CONJECTURE,exact,
allamanis2019survey,10.1145/3212695,crossref,A Survey of Machine Learning for Big Code and Naturalness,exact,key renamed from allamanis2018survey to match year of record
bernstein2017pqc,10.1038/nature23461,crossref,Post-quantum cryptography,exact,
shor1997algorithms,10.1137/S0097539795293172,crossref,Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer,exact,
nist2024fips203,10.6028/NIST.FIPS.203,crossref,Module-lattice-based key-encapsulation mechanism standard,exact,
nist2024fips204,10.6028/NIST.FIPS.204,crossref,Module-lattice-based digital signature standard,exact,
nist2024fips205,10.6028/NIST.FIPS.205,crossref,Stateless hash-based digital signature standard,exact,
kocher2019spectre,10.1109/SP.2019.00002,crossref,Spectre Attacks: Exploiting Speculative Execution,exact,
lipp2020meltdown,10.1145/3357033,crossref,Meltdown: reading kernel memory from user space,exact,title+subtitle fields
biggio2018wild,10.1016/j.patcog.2018.07.023,crossref,Wild patterns: Ten years after the rise of adversarial machine learning,exact,
carlini2017robustness,10.1109/SP.2017.49,crossref,Towards Evaluating the Robustness of Neural Networks,exact,
dwork2006calibrating,10.1007/11681878_14,crossref,Calibrating Noise to Sensitivity in Private Data Analysis,exact,
dwork2014algorithmic,10.1561/0400000042,crossref,The Algorithmic Foundations of Differential Privacy,exact,
abadi2016dpsgd,10.1145/2976749.2978318,crossref,Deep Learning with Differential Privacy,exact,
kairouz2021fl,10.1561/2200000083,crossref,Advances and Open Problems in Federated Learning,exact,
gentry2009fhe,10.1145/1536414.1536440,crossref,Fully homomorphic encryption using ideal lattices,exact,
bonneau2015sok,10.1109/SP.2015.14,crossref,SoK: Research Perspectives and Challenges for Bitcoin and Cryptocurrencies,exact,
amershi2019guidelines,10.1145/3290605.3300233,crossref,Guidelines for Human-AI Interaction,exact,
shneiderman2020hcai,10.1080/10447318.2020.1741118,crossref,"Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy",exact,title+subtitle fields
yang2020reexamining,10.1145/3313831.3376301,crossref,"Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design",exact,
mildenhall2020nerf,10.1007/978-3-030-58452-8_24,crossref,NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis,exact,
tewari2020neural,10.1111/cgf.14022,crossref,State of the Art on Neural Rendering,exact,
kerbl2023gaussian,10.1145/3592433,crossref,3D Gaussian Splatting for Real-Time Radiance Field Rendering,exact,
baek2021rosettafold,10.1126/science.abj8754,crossref,Accurate prediction of protein structures and interactions using a three-track neural network,exact,
senior2020alphafold,10.1038/s41586-019-1923-7,crossref,Improved protein structure prediction using potentials from deep learning,exact,
lin2023esm,10.1126/science.ade2574,crossref,Evolutionary-scale prediction of atomic-level protein structure with a language model,exact,
abramson2024af3,10.1038/s41586-024-07487-w,crossref,Accurate structure prediction of biomolecular interactions with AlphaFold 3,exact,
bosshart2014p4,10.1145/2656877.2656890,crossref,P4: programming protocol-independent packet processors,exact,title+subtitle fields
mckeown2008openflow,10.1145/1355734.1355746,crossref,OpenFlow: enabling innovation in campus networks,exact,title+subtitle fields
langley2017quic,10.1145/3098822.3098842,crossref,The QUIC Transport Protocol: Design and Internet-Scale Deployment,exact,title+subtitle fields
shi2016edge,10.1109/JIOT.2016.2579198,crossref,Edge Computing: Vision and Challenges,exact,
kraska2018learned,10.1145/3183713.3196909,crossref,The Case for Learned Index Structures,exact,
malkov2020hnsw,10.1109/TPAMI.2018.2889473,crossref,Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs,exact,
johnson2021faiss,10.1109/TBDATA.2019.2921572,crossref,Billion-Scale Similarity Search with GPUs,exact,
karpukhin2020dpr,10.18653/v1/2020.emnlp-main.550,crossref,Dense Passage Retrieval for Open-Domain Question Answering,exact,
raissi2019pinn,10.1016/j.jcp.2018.10.045,crossref,Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,exact,
karniadakis2021piml,10.1038/s42254-021-00314-5,crossref,Physics-informed machine learning,exact,
wang2023aiscience,10.1038/s41586-023-06221-2,crossref,Scientific discovery in the age of artificial intelligence,exact,
masanet2020datacenter,10.1126/science.aba3758,crossref,Recalibrating global data center energy-use estimates,exact,
bai1998breaks,10.2307/2998540,crossref,Estimating and Testing Linear Models with Multiple Structural Changes,exact,
bai2003computation,10.1002/jae.659,crossref,Computation and analysis of multiple structural change models,exact,
bernal2016its,10.1093/ije/dyw098,crossref,Interrupted time series regression for the evaluation of public health interventions: a tutorial,exact,key renamed from bernal2017its to match year of record
andrews1993tests,10.2307/2951764,crossref,Tests for Parameter Instability and Structural Change With Unknown Change Point,exact,
killick2012pelt,10.1080/01621459.2012.737745,crossref,Optimal Detection of Changepoints With a Linear Computational Cost,exact,
kobak2025delving,10.1126/sciadv.adt3813,crossref,Delving into LLM-assisted writing in biomedical publications through excess vocabulary,exact,
dwivedi2023sowhat,10.1016/j.ijinfomgt.2023.102642,crossref,"Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy",minor,Crossref title prefixed 'Opinion Paper:'; record matches
vannoorden2023survey,10.1038/d41586-023-02980-0,crossref,"AI and science: what 1,600 researchers think",exact,
messeri2024illusions,10.1038/s41586-024-07146-0,crossref,Artificial intelligence and illusions of understanding in scientific research,exact,
birhane2023science,10.1038/s42254-023-00581-4,crossref,Science in the age of large language models,exact,
krenn2023forecasting,10.1038/s42256-023-00735-0,crossref,Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network,exact,
fortunato2018sos,10.1126/science.aao0185,crossref,Science of science,exact,
wang2021sos,10.1017/9781108610834,crossref,The Science of Science,exact,
park2023disruptive,10.1038/s41586-022-05543-x,crossref,Papers and patents are becoming less disruptive over time,exact,
chu2021slowed,10.1073/pnas.2021636118,crossref,Slowed canonical progress in large fields of science,exact,
bornmann2015growth,10.1002/asi.23329,crossref,Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references,exact,
binnashwan2023chatgpt,10.1016/j.techsoc.2023.102370,crossref,Use of ChatGPT in academia: Academic integrity hangs in the balance,exact,
kapoor2023leakage,10.1016/j.patter.2023.100804,crossref,Leakage and the reproducibility crisis in machine-learning-based science,exact,
gundersen2018reproducibility,10.1609/aaai.v32i1.11503,crossref,State of the Art: Reproducibility in Artificial Intelligence,exact,
openai2022chatgpt,https://openai.com/blog/chatgpt,url,Introducing ChatGPT,exact,Wayback snapshot 2022-12-02 (status 200); live URL openai.com/index/chatgpt/ snapshot 2025-01-02
openalex2025topics,https://help.openalex.org/data/topics/,url,Topics (OpenAlex documentation),exact,HTTP 200 on 2026-11-03
arxiv2026stats,https://arxiv.org/stats/monthly_submissions,url,arXiv monthly submissions,exact,HTTP 200 on 2026-11-03