Theme All AI for science AI paradigms & knowledge representation Agent development Agent planning & cognitive architectures Agent reliability & evaluation Economics & adoption Embodied AI & world models Human-AI interaction Human–AI interaction & adoption Infrastructure & efficiency Infrastructure, efficiency & open ecosystems Language models & representation Machine learning foundations Machine-learning foundations Model evaluation & UX Multi-agent coordination Multi-agent systems Open ecosystem & education Physical AI & world models Reliability, uncertainty & evaluation Safety & alignment Safety, security & alignment Security & alignment
School / paradigm All AI safety / control Accelerated computing Accelerated deep learning Adversarial machine learning Adversarial machine learning / security Agent evaluation / task horizons Artificial life / swarm behavior Attention / sequence modeling Automated theorem proving Autoregressive scaling / in-context learning Behavioral decision research Belief-desire-intention Bidirectional representation learning Blackboard / opportunistic problem solving Case investigation of radiation overdoses between 1985 and 1987 involving software races, interface design, organizational failures, and weak incident reporting Classical planning Closed-loop automated science Cognitive engineering Cognitive science / grounding Computational learning theory Computational motor control Computational neuroscience / representation Computer security Connectionism Connectionism / adaptive filtering Connectionist / representation learning Connectionist / supervised deep learning Connectionist sequence learning Convolutional neural networks Cooperative multi-agent reinforcement learning Cybernetics / control ethics Cybernetics / optimal control Cybernetics and control Dataflow systems / open-source infrastructure Deep generative learning Differentiable memory / connectionist computation Differentiable memory / hybrid computation Distributed AI / organizational metaphor Distributed AI and swarm intelligence Distributed machine learning Distributed systems Distributed systems / memory optimization Distributional semantics Distributional semantics / neural language modeling Documentation / accountable AI Ensemble learning Ensemble learning / uncertainty Evolutionary computation Expert systems / approximate uncertainty Field experiment / labor economics Game theory / evolutionary dynamics Generative modeling / score matching Graph learning / active scientific discovery Heuristic discovery Human augmentation Human augmentation and sociotechnical systems Human factors / function allocation Human factors / measurement Human factors of automation Human feedback / post-training Human-computer interaction Human-computer interaction / labor economics Human–AI collaboration / decision theory IO-aware algorithms / accelerator kernels Inductive logic programming Industrial expert systems Inference serving / memory management Information systems adoption Information-flow security / agent control Information-processing psychology Integrated learning and planning Knowledge engineering / expert systems Labor economics / task framework Language-agent reasoning and acting Large-scale datasets / benchmarking Large-scale symbolic knowledge Latent dynamics / model-based control Latent world modeling / planning Long-run AI safety Model-based reinforcement learning Model-based reinforcement learning / search Multi-agent benchmark Multi-agent reinforcement learning Multi-agent scientific reasoning Multi-metric evaluation Neural language modeling Neuro-symbolic / probabilistic logic Neuro-symbolic theorem proving Open ML software Open deep-learning software Open model ecosystem / reinforcement learning Open-ended embodied agents Optimization theory Organizational complements Parallel computer architecture Parallel computing Philosophy of mind / critique of strong AI Population-based multi-agent reinforcement learning Predictive processing Preference learning / alignment Probabilistic AI Probabilistic robotics Probabilistic robotics / autonomous systems Reactive / embodied robotics Recurrent neural networks Reinforcement learning Reinforcement learning and adaptive agents Robust learning theory Robust machine learning Rule-based expert systems Rule-guided alignment / AI feedback Safety, security, and machine ethics Scaling laws / empirical optimization Scientific machine learning Scientific machine learning / molecular interactions Scientific machine learning / structural biology Search + reinforcement learning Semiconductor scaling Shared datasets / empirical ML Situated / embodied AI Situated, embodied, and enactive AI Social learning / multi-agent evaluation Social simulation / language agents Statistical NLP Statistical and probabilistic AI Statistical evaluation / uncertainty Statistical learning / kernel methods Statistical pattern recognition Structured symbolic knowledge Swarm intelligence Swarm robotics Symbolic AI / GOFAI Symbolic NLP / microworld semantics Symbolic critique of connectionism Symbolic dialogue / pattern matching Symbolic problem solving Symbolic robotics Unified cognitive architecture Vision-language-action learning
Researcher or lab All Adrian Roitberg Ajay Jain Alberto Colorni Alex Graves Alex Graves; Greg Wayne; Ivo Danihelka Alex Graves; Greg Wayne; Malcolm Reynolds; Ivo Danihelka; DeepMind team Alex Krizhevsky Alex Krizhevsky; Ilya Sutskever; Geoffrey Hinton Alexander Pritzel Allen Newell Allen Newell; Herbert Simon; J. C. Shaw Amil Merchant Amil Merchant and collaborators Anand Madhavan Anand Rao Andrew Donkin Andrew Ng Angelika Kimmig Anthony Brohan Anthony Brohan and collaborators Anthony Joseph Ashish Vaswani Ashish Vaswani and collaborators Ashwin Srinivasan Balaji Lakshminarayanan Balaji Lakshminarayanan; Alexander Pritzel; Charles Blundell Ben Shneiderman Berkeley Dietvorst Berkeley Dietvorst; Joseph Simmons; Cade Massey Bernard Widrow Bernard Widrow; Marcian Hoff Blaine Nelson Bruce Buchanan Bruce Buchanan; Edward Feigenbaum; Joshua Lederberg Butler Lampson Cade Massey Carl Djerassi Carrie Cai Charles Blundell Charles Rosen Charles Rosen; Nils Nilsson; Peter Hart; Richard Fikes Chris Olah Christian Jauvin Christian Szegedy Christopher Bryant Christopher Watkins Christopher Watkins; Peter Dayan Christopher Wickens Chuan Guo Chuan Guo; Geoff Pleiss; Yu Sun; Kilian Weinberger Clark Turner Corinna Cortes Corinna Cortes; Vladimir Vapnik Craig Reynolds D. Raj Reddy Dan Mané Dana Ballard Daniel Wolpert Daniel Wolpert; Zoubin Ghahramani; Michael Jordan Danielle Li Danijar Hafner Danijar Hafner and collaborators Danijar Hafner; Timothy Lillicrap; Ian Fischer; Mohammad Norouzi Dario Amodei Dario Amodei; Chris Olah; Jacob Steinhardt; Paul Christiano; John Schulman; Dan Mané Dario Floreano David Aha David Autor David Autor; Frank Levy; Richard Murnane David Ha David Ha; Jürgen Schmidhuber David Israel David Kibler David Marr David Rumelhart David Rumelhart; Ronald Williams David Silver David Silver and collaborators David Warde-Farley David Wolpert DeepMind team DeepSeek-AI Deepak Verma Douglas Engelbart Douglas Kell Douglas Lenat Edoardo Debenedetti Edoardo Debenedetti and collaborators Edward Feigenbaum Edward Shortliffe Edward Shortliffe; Randall Davis Eiichi Osawa Eric Horvitz Erik Brynjolfsson Erik Brynjolfsson; Danielle Li; Lindsey Raymond Fei-Fei Li Ffion Jones Francesco Mondada Frank Levy Fred Davis Frederick Hayes-Roth Frédéric Bastien Gene M. Amdahl Geoff Pleiss Geoffrey Hinton Geoffrey Holmes George Furnas Gordon E. Moore Greg Corrado Greg Wayne Guanzhi Wang Guanzhi Wang and collaborators Guillaume Desjardins H. T. Kung Herbert A. Simon Hiroaki Kitano Hitoshi Matsubara Hugh Durrant-Whyte Ian Fischer Ian Goodfellow Ian Goodfellow; Jonathon Shlens; Christian Szegedy Ian Witten Ilya Sutskever Itsuki Noda Ivo Danihelka J. Alan Robinson J. C. Shaw J. D. Tygar Jacob Devlin Jacob Devlin; Ming-Wei Chang; Kenton Lee; Kristina Toutanova Jacob Steinhardt James Bergstra Jan Černocký Jeffrey Dean Jeffrey Dean and collaborators Jeffrey Dean; Sanjay Ghemawat Jeffrey Elman Jem Rowland Jennifer Lai Jia Deng Jia Deng; Fei-Fei Li and ImageNet team Jian Sun Joel Leibo Joel Leibo and collaborators John Brooke John Holland John Jumper John Jumper and collaborators John Laird John Laird; Paul Rosenbloom John McDermott John Schulman John Searle Jonathan Ho Jonathan Ho; Ajay Jain; Pieter Abbeel Jonathon Shlens Joon Sung Park Joon Sung Park; Joseph O'Brien; Carrie Cai; Meredith Ringel Morris; Percy Liang; Michael Bernstein Jordan Hoffmann Jordan Hoffmann and collaborators Joseph O'Brien Joseph Simmons Joseph Turian Joseph Weizenbaum Josh Abramson Josh Abramson and collaborators Joshua Lederberg Judea Pearl Julian Schrittwieser Julian Schrittwieser and collaborators Juraj Gottweis Juraj Gottweis and collaborators Justin Smith Justin Smith; Olexandr Isayev; Adrian Roitberg Jürgen Schmidhuber Kai Chen Kai Li Kaiming He Kaiming He; Xiangyu Zhang; Shaoqing Ren; Jian Sun Kenneth J. Biba Kenneth Whelan Kenton Lee Kilian Weinberger Kristina Toutanova Lee Erman Leo Breiman Leslie Valiant Li-Jia Li Lindsey Raymond Long Ouyang Long Ouyang and collaborators Lorin Hitt Luc De Raedt Luca Gambardella Lukáš Burget Léon Bottou Malcolm Reynolds Marcian Hoff Marco Barreno Marco Dorigo Margaret Mitchell Margaret Mitchell and collaborators Martha Pollack Martin Karafiát Martín Abadi Martín Abadi and collaborators Marvin Minsky Marvin Minsky; Seymour Papert Mausam Megan Kinniment Megan Kinniment and collaborators Meredith Ringel Morris Michael Bernstein Michael Bratman Michael Bratman; David Israel; Martha Pollack Michael Georgeff Michael Jordan Michael Kearns Michael Kearns; Ming Li Michael Montemerlo Michael Sternberg Michael Young Ming Li Ming-Wei Chang Minoru Asada Mohammad Norouzi NVIDIA engineering Nancy Leveson Nilesh Dalvi Nilesh Dalvi; Pedro Domingos; Mausam; Sumit Sanghai; Deepak Verma Nils Nilsson Norbert Wiener Olexandr Isayev Olivier Breuleux Oriol Vinyals Oriol Vinyals and collaborators Pascal Lamblin Pascal Vincent Patrick Haffner Paul Christiano Paul Christiano and collaborators Paul Rosenbloom Pedro Domingos Percy Liang Percy Liang and collaborators Peter Brown Peter Brown; Robert Mercer and IBM team Peter Dayan Peter Hart Peter deSouza Philip Reiser Pieter Abbeel Raja Parasuraman Raja Parasuraman; Christopher Wickens; Thomas Sheridan Rajat Raina Rajat Raina; Anand Madhavan; Andrew Ng Rajesh Rao Rajesh Rao; Dana Ballard Randall Davis Razvan Pascanu Reid G. Smith Richard Fikes Richard Harshman Richard Murnane Richard Socher Richard Sutton Robert Axelrod Robert Mercer Robert Schapire Robin Manhaeve Robin Manhaeve; Sebastijan Dumancic; Angelika Kimmig; Thomas Demeester; Luc De Raedt Rodney Brooks Ronald Williams Ross King Ross King; Stephen Oliver Rudolf E. Kalman Russell Sears Ryan Lowe Ryan Lowe and collaborators Réjean Ducharme Saleema Amershi Saleema Amershi and collaborators Samyam Rajbhandari Samyam Rajbhandari and collaborators Sanjay Ghemawat Sanjeev Khudanpur Scott Deerwester Sebastian Thrun Sebastian Thrun and Stanford Racing Team Sebastijan Dumancic Sepp Hochreiter Sepp Hochreiter; Jürgen Schmidhuber Seymour Papert Shakked Noy Shakked Noy; Whitney Zhang Shaoqing Ren Shunyu Yao Shunyu Yao and collaborators Simon Osindero Stefano Nolfi Stephen Muggleton Stephen Oliver Stephen Omohundro Stevan Harnad Stuart Card Stuart Card; Thomas Moran Sumit Sanghai Susan Dumais Susan Dumais; Scott Deerwester; George Furnas; Thomas Landauer Tabish Rashid Tabish Rashid and collaborators Terry Winograd Thomas Cover Thomas Cover; Peter Hart Thomas Demeester Thomas Landauer Thomas Moran Thomas Sheridan Tim Bailey Timothy Bresnahan Timothy Lillicrap Tom Brown Tom Brown and collaborators Tomas Mikolov Tomas Mikolov; Kai Chen; Greg Corrado; Jeffrey Dean Tomáš Mikolov Tomáš Mikolov and collaborators Tri Dao Tri Dao and collaborators Trieu Trinh Trieu Trinh and collaborators Victor Lesser Victor Lesser; Lee Erman; Frederick Hayes-Roth; D. Raj Reddy Victor Riley Vincent Della Pietra Vittorio Maniezzo Vladimir Vapnik Wei Dong Whitney Zhang William D. Hamilton William Macready Woosuk Kwon Woosuk Kwon and collaborators Xiangyu Zhang Yann LeCun Yann LeCun; Léon Bottou; Patrick Haffner Yasuo Kuniyoshi Yee-Whye Teh Yoav Freund Yoav Freund; Robert Schapire Yoshua Bengio Yu Sun Yuntao Bai Yuntao Bai and collaborators Zoubin Ghahramani collaborators colleagues investigators operators, regulators, research community team the SWARM-BOTS team the Stanford Racing Team the UCI community the Waikato team
Evidence maturity All A rule-based system generated and evaluated mathematical concepts from heuristics, discovering familiar structures from set-theoretic primitives A single machine-oriented inference rule for first-order logic refutation Adaptive switching circuits trained with a least-mean-squares error rule Algorithm + StarCraft II benchmark Algorithm + hardware benchmarks Algorithm + image benchmarks Algorithm + simulated control Algorithm + simulation Analytical bound on speedup when only a fraction of a workload can be parallelized Analytical essay on goal-directed machines and social consequences Analyzed PAC learning when an adversary can corrupt a fraction of examples Analyzed modular IF-THEN rules, control, explanation, and knowledge acquisition in a clinical consultant Analyzed occupational task inputs from 1960–1998 and modeled computers as substitutes for routine tasks and complements for nonroutine cognitive work Applied truncated singular-value decomposition to term-document matrices for retrieval Architecture + benchmark experiment Architecture + translation benchmarks Architecture separated beliefs, desires, intentions, plan generation, filtering, and execution monitoring Artificial ants constructed solutions and reinforced shared pheromone trails on traveling-salesperson instances Asymptotic analysis of a classifier that labels a point by its nearest stored example Automatically clustered words into classes and estimated sequence probabilities from class transitions and word-within-class probabilities Autonomous vehicle combined probabilistic state estimation, machine-learned terrain perception, laser mapping, planning, and control over a 132-mile desert course Averaged optimization performance over all possible objective functions Benchmark Benchmark + taxonomy Benchmark experiment Benchmark study Benchmark suite Built a WordNet-organized image database with millions of labeled images and introduced large-scale visual recognition tasks Built complete mobile creatures from parallel activity-producing systems coupled directly to the world CASP14 blind prediction Combined production rules with certainty factors for antimicrobial-therapy consultation under incomplete information Combined randomized decision trees trained on bootstrap samples and random feature subsets Commentary Compared command interaction with visible objects, rapid reversible actions, and incremental feedback Compiled symbolic mathematical expressions, automatic differentiation, and CPU/GPU kernels for machine learning research Computational chemistry experiment Computer tournaments and evolutionary analysis of repeated prisoner's dilemma strategies Conceptual analysis of how formal symbols acquire intrinsic meaning rather than meaning only through other symbols Controlled human experiments Controlled scaling study Created a public collection of datasets used to compare learning algorithms across common tasks Decision-theoretic argument that capable goal-directed systems may instrumentally seek resources, self-preservation, efficiency, and goal protection Decomposed skilled interaction into goals, operators, methods, and selection rules and predicted task time Defined an information-flow model designed to prevent unauthorized lowering of data integrity Defined learnability by sample complexity, computational efficiency, accuracy, and confidence under a distribution Derived logic programs from examples plus background knowledge using inverse entailment and hypothesis search Directed graphical models represented conditional independencies and supported belief updating under uncertainty Directory signal Distributed nodes announced tasks, submitted bids, awarded contracts, and reported results Empirical benchmark + trend model Empirical trend extrapolation from integrated-circuit component counts and costs Encoded chemical constraints and expert heuristics to infer molecular structures from mass-spectrometry data Evaluated an RNN next-word model and mixtures on speech-recognition corpora against strong backoff n-grams Field report Firm-level empirical study related IT adoption to decentralized work practices, skill, and productivity Formalized genetic algorithms using selection, crossover, mutation, and schemata over populations of candidate solutions Formalized how a service containing a secret might leak it through overt or covert channels Formalized rational agents with beliefs, goals, intentions, events, and commitment strategies Framework + case studies Greedy layer-wise unsupervised training initialized deep networks before supervised fine-tuning Guideline synthesis + validation Hierarchical model predicted lower-level neural activity and propagated residual errors; trained on natural images Human-in-the-loop experiments Independent knowledge sources posted partial hypotheses to a shared blackboard under a control strategy in speech understanding Introduced gated memory cells and constant-error flow to address vanishing gradients on long temporal dependencies Iteratively reweighted training examples and combined weak hypotheses into a weighted vote Large field study Large-scale model + benchmarks Layered asynchronous behaviors directly coupled perception to action in mobile robots Learned continuous word vectors jointly with a feedforward next-word probability model and evaluated on text corpora Learned relational rules predicting mutagenicity from atoms and bond connectivity and compared them with established chemical methods Long-running effort to encode commonsense facts and rules in a formal ontology and inference system Mathematical analysis of single-layer perceptrons and representational limits Maximized the margin between classes and used kernels to fit nonlinear decision boundaries Means-ends analysis over symbolically described operators, goals, and differences Mobile robot integrated perception, world modeling, planning, and action in a simplified rooms-and-blocks environment Model + corpus experiment Model + density-functional validation Model card Modeled classification as a game in which a cost-sensitive adversary modifies examples to evade a learned classifier Multilayer networks adjusted weights by propagating output error gradients backward Natural-language dialogue grounded in a simulated blocks world with parsing, reference resolution, planning, and memory Off-policy temporal-difference control learned action values from sampled transitions without a model of the environment Outlined principles and systems in which people and automated services dynamically share initiative under uncertainty Parallelized deep belief networks and sparse coding on graphics processors and compared them with multicore CPU implementations Participants moved a hand in darkness under external forces; the temporal propagation of localization errors was compared with optimal state-estimation predictions Partnership announcement Peer-reviewed Peer-reviewed benchmark study Peer-reviewed cross-domain experiments Peer-reviewed experiments Peer-reviewed game experiment Peer-reviewed olympiad benchmark Peer-reviewed system experiment Podcast Predicted future reward and updated estimates from successive predictions without waiting for a final outcome Preference-learning experiment Preprint Preprint + AgentDojo evaluation Preprint + Minecraft evaluation Preprint + game experiments Preprint + model experiments Preprint + synthetic tasks Pretraining + downstream benchmarks Product/technical note Production rules configured VAX computer orders from customer requirements and component constraints Production system used problem spaces, universal subgoaling, and chunking to learn rules from impasses Program announcement Programming model and runtime automatically partitioned, scheduled, retried, and combined large key-value computations across commodity clusters Programming platform exposed massively parallel GPU hardware through a general-purpose C-like model Prompting + interactive benchmarks Proposed robot soccer as a standard, dynamic, adversarial testbed integrating perception, action, learning, and teamwork Proposed slot-filled data structures for stereotyped situations, defaults, and expectations Published paper Randomized controlled experiment Regular arrays of processing elements streamed data through local, synchronized computations Released a common interface for preprocessing, classification, clustering, feature selection, and comparative experiments Represented actions with preconditions and effects; searched for an operator sequence that transforms an initial world model into a goal state Research agenda Robot formulated hypotheses about yeast gene function, designed and executed experiments, and generated novel functional findings Robot-learning experiment Rule-based text transformations that mirrored user statements without semantic world knowledge Scientific platform / product report Scientific platform / technical report Separated computational goals, algorithms/representations, and physical implementation; developed primal sketch and 2.5-D representations Showed that catastrophic failures emerge from system interactions, not a single bad component, and that software safety requires process and organizational controls. Simulated flocking from local separation, alignment, and cohesion rules without a global controller Small mobile robots physically connected and coordinated to traverse terrain and transport objects Survey-based model linked perceived usefulness and perceived ease of use to adoption intentions and system use Synthesized empirical evidence on overreliance, rejection, complacency, trust, and operator monitoring System + benchmark experiments System + human evaluation System card / benchmark System generated gene-function hypotheses, selected experiments, executed yeast growth assays with a laboratory robot, interpreted outcomes, and iterated System-design framework followed by NLS implementation and the 1968 public demonstration Systems paper Systems paper + large-model experiments Systems paper + release Systems paper + serving benchmarks Taxonomy organized attacks by influence, security violation, and specificity and analyzed spam, intrusion, and other learning systems Technical report Technical report / formal artifact Ten-item post-use questionnaire designed as a quick, technology-independent usability measure Ten-level framework distinguished information acquisition, analysis, decision selection, and action implementation Theory + attack experiments Theory + numerical examples Think-aloud protocols and computer models of puzzle solving, including means-ends analysis Thought experiment separating rule-following symbol manipulation from semantic understanding Trained a recurrent network to predict the next element in structured sequences and analyzed its hidden-state organization Trained convolutional networks end to end on handwritten digit recognition and integrated them into document-processing systems Tutorial synthesis of simultaneous localization and mapping methods and implementations Used learned experience both to update a value/policy and to train a model that generates simulated planning updates Vendor preprint + released weights Vendor-affiliated preprint + selected validation
Source tier All Tier A Tier B Tier C
Era All 1960s (13) 1970s (10) 1980s (22) 1990s (23) 2000s (18) 2010s (27) 2020s (90)
