Corrections
When we get something substantively wrong, we fix it and log the fix here; small copyedits live in each article's revision history instead. Found an error? Use the "Report issue" button on the article (no account needed); we aim to review every report within 72 hours. See the verifiability policy for how checking works.
- GPT Storeeditorial
rebuild GPT Store history, publishing, privacy, and research claims
- Transfer Learningeditorial
independently reverify transfer learning evidence boundaries, adaptation results, and source metadata
- Knowledge Distillationeditorial
independently reverify knowledge distillation objectives, evidence boundaries, failure modes, and source metadata
- GSM8Keditorial
rebuild GSM8K size, protocol, contamination, and reliability claims
- Generative adversarial networkeditorial
independently reverified GAN article; fixes BigGAN variant and resolution benchmark values, states theorem assumptions, replaces unsupported claims with 30 explicit primary or peer-reviewed sources, and adds bounded training, evaluation, application, and risk coverage.
- Tsinghua Universityeditorial
Rebuild Tsinghua University around dated official records; distinguish university units from BAAI, Zhipu, and research collaborations; remove unsupported rankings, founder-share, export-control, and promotional claims.
- Scale AIeditorial
clarify Meta deal, contract, labor, leadership, and valuation claims
- Vision language modeleditorial
replaced volatile model and leaderboard claims with source-bounded coverage of VLM architectures, training, evaluation, limitations, and deployment
- Microsoft Researcheditorial
removed unsupported current staff, budget, lab, leadership, product-attribution, impact, and superlative claims; replaced them with dated organization records and bounded primary evidence
- Google Cloudeditorial
distinguish Google Cloud from GCP and fix financial and Wiz figures
- Groq LPUeditorial
consolidate the duplicate Groq LPU article into the independently verified Groq Hardware article.
- Groq Hardwareeditorial
remove the reciprocal Groq LPU link before consolidating that duplicate article into Groq Hardware
- Carnegie Mellon Universityeditorial
fixed Logic Theorist attribution, SCS and HCII chronology, SCS department structure, Robotics Institute funding, Navlab autonomy scope, dated institutional figures, and invalid internal links
- Custom GPTeditorial
fix Custom GPT access, privacy, and adoption claims
- Decision Treeeditorial
fixed THAID date and NP-completeness scope; qualified missing-data, categorical, interpretability, probability, importance, complexity, and ensemble claims
- AI Alignmenteditorial
Rebuilt AI Alignment around 25 authoritative sources; removed unsupported risk claims; fixed EU source fit and reference rendering.
- Social Mediaeditorial
Reframed Social Media as a broad socio-technical system; replaced unsupported claims with 34 explicit sources; corrected a 2026 Nature citation and reference rendering.
- Random Foresteditorial
replaced false overfitting, out-of-bag, importance, default, and benchmark claims; added 26 explicit academic and first-party sources
- UBTECH Roboticseditorial
fixed Walker specifications, financing classifications, FY2025 results, shipment ranking, dated company metrics, and promotional claims; added primary-source URLs and July 2026 deployment updates
- AI Agentseditorial
Repaired 28 bibliography emphasis spans that rendered as literal Markdown markers; factual prose, citations, source text, URLs, internal links, and categories are unchanged.
- Meta AIeditorial
Added Muse Image privacy and chatbot safety-governance coverage
- Natural Language Processingeditorial
Repaired visible reference-title emphasis while leaving prose, claims, citations, links, source text, and categories unchanged.
- Computer Visioneditorial
Repair Mask R-CNN source link and reference emphasis rendering.
- Language Modeleditorial
Repaired 34 bibliography emphasis spans that rendered as literal Markdown markers
- Language Modeleditorial
Added state-space and diffusion language-model architecture and objective coverage
- Hugging Faceeditorial
clarified a security-study term and tightened supporting citations for Transformers, BLOOM, and model supply-chain research.
- OpenAI o1editorial
Reconstructed OpenAI o1 from primary and independent evidence; corrected full o1 context to 200K; removed unverified architecture, parameter, codename, genealogy, reward, market, and successor claims; separated o1-preview, research o1, API snapshot, and o1-pro results; added exact evaluation protocols, safety-test scope, API lifecycle dates, independent benchmark caveats, and explicit sources.
- HumanEvaleditorial
Rewrites the article around the original 164-task Python benchmark, corrects pass@k provenance and score interpretation, separates later variants, removes unverified leaderboard claims, and replaces broken footnotes with verified numeric citations.
- AgiBoteditorial
distinguish AgiBot production milestones, shipment estimates, disclosed deployments, bounded research results, artifact-specific licensing, and product security support.
- Amazon Web Serviceseditorial
Reconstructed AWS as Amazon's cloud segment and service platform; corrected the 2025 operating-income share and Amazon/AWS capex boundaries; date-stamped 2026 segment and Region data; bounded the Anthropic investment to primary evidence; removed unsupported market, customer, capacity, project, catalogue, and forecast claims; and added explicit primary, academic, standards, government, regulator, security, architecture, and incident sources.
- Open-source AIeditorial
distinguished open-source AI from open-weight and source-available releases; verified OSAID 1.0 components, licensing boundaries, reproducibility, safety, and EU AI Act exceptions; removed unsupported model rankings, download shares, forecasts, cost claims, and vendor comparisons.
- LangChaineditorial
reconstruct LangChain with cutoff-pinned package versions, exact product boundaries, and sourced coverage of agents, tools, retrieval, memory, licensing, deployment, and security.
- Agentic AIeditorial
rebuilt Agentic AI around documented definitional disagreement, classical agent foundations, verified architectures and benchmarks; removed unsupported adoption, market, ROI, current-leaderboard, and NIST-specific claims; added bounded security and governance evidence with canonical links.
- LoRA (Low-Rank Adaptation)editorial
Reconstructed LoRA's definition, mathematics, initialization, scaling, targeting, efficiency boundaries, original evidence, variants, QLoRA, serving, composition, reproducibility, and limitations; corrected the Prefix-Tuning comparison and bounded the NeurIPS 2025 spectral comparison; removed unsupported deployment, popularity, and universal-performance claims.
- Learning Rateeditorial
Rebuilds Learning Rate around assumption-bounded optimization theory, primary-source evidence, reproducible tuning guidance, correctly rendered schedules, and explicit limits on universal prescriptions.
- Self-attentioneditorial
Rebuilds Self-attention around precise scaled dot-product and multi-head computation, masks, position mechanisms, complexity, decoding, efficient variants, applications, interpretability limits, and historical antecedents using 29 primary or peer-reviewed sources.
- Test Seteditorial
defines a test set as an evaluation sample reserved from fitting and selection, ties its claims to a target population and protocol, and documents leakage-resistant splitting, precision-based sizing, nested assessment, uncertainty, distribution shift, benchmark reuse, label error, and LLM contamination.
- NVIDIA Blackwelleditorial
independently verifies NVIDIA Blackwell's product-family boundaries, release and production history, GB100 and RTX distinctions, memory and compute-capability specifications, platform topology, numerical formats, security, measured performance, power requirements, and status through July 28, 2026.
- Machine Translationeditorial
Reconstructed the history, principal paradigms, training methods, multilingual and LLM translation, evaluation, speech translation, reliability, and post-editing; corrected unsupported product, ranking, market, and source-version performance claims.
- Logistic Regressioneditorial
Rebuilds the Logistic Regression article around the verified binary model, likelihood, coefficient interpretation, separation, regularization, diagnostics, evaluation, extensions, and current software behavior; removes unsupported universal calibration, threshold, sample-size, importance, and performance claims.
- JAXeditorial
independently verifies and updates JAX's release status, program-transformation model, compiler and sharding architecture, platform support, ecosystem boundaries, bounded use cases, performance methodology, and citation traceability.
- Actuatoreditorial
Reframe Actuator as a general energy-to-motion device, distinguish transducer, transmission, sensing, and control boundaries, replace unsupported supplier and universal performance claims with primary and peer-reviewed evidence, and add scoped selection, safety, and robotics guidance.
- Quantizationeditorial
Restores general quantization scope; corrects neural-network methods, equations, data-format claims, and deployment caveats.
- Stochastic Gradient Descent (SGD)editorial
independently verifies and updates Robbins-Monro conditions, sampling assumptions, convergence scope, noise and flatness claims, batch scaling, and distributed-SGD boundaries.
- Hyperparametereditorial
independently verifies and updates Hyperparameter definitions, dynamic and data-dependent selection, search-space and fidelity scope, validation bias, interaction claims, transfer limits, and citation traceability.
- Long Short-Term Memory (LSTM)editorial
Rebuilds the LSTM article around the verified cell equations, gradient behavior, history, variants, training, bounded applications, framework behavior, and documented limitations; removes unsupported dominance, deployment, control-application, citation-count, and performance claims.
- Imitation Learningeditorial
independently verifies and updates Imitation Learning history, method distinctions, theory, benchmark scope, and modern robot-learning publication evidence against 31 primary and peer-reviewed sources.
- Venture Capitaleditorial
Rebuilds the article around fund structure, investment process, financing instruments, valuation, performance, exits, innovation evidence, public policy, and a bounded OECD-sourced AI market section; removes speculative company-level financing claims.
- Vision-language-action modeleditorial
independently verifies and rebuilds Vision-language-action model scope, chronology, architectures, datasets, benchmark definitions, source-version discrepancies, evidence limits, safety, and artifact openness.
- Interpretabilityeditorial
independently verifies interpretability methods, evidence limits, legal scope and application dates, and mechanistic-interpretability claims against 45 primary, official, and peer-reviewed sources.
- Hallucinationeditorial
Replaces unsupported and overgeneralized claims; distinguishes factuality, faithfulness, and confabulation; scopes benchmark results; and corrects legal-study denominators with primary evidence.
- GPT-4oeditorial
resolved undefined citation markers, bounded architectural-disclosure claims, added independent multimodal evaluations, and documented GPT-4o API deprecation
- Agility Roboticseditorial
Rebuilt Agility Robotics coverage with sequential citations, scoped deployment evidence, site-specific safety qualification, and current 2026 corporate facts
- xAIeditorial
distinguish xAI from its parent's broader AI segment, correct corporate, financing, product, compute, and contract claims, and remove unsupported projections.
- PaLMeditorial
rebuild PaLM from primary sources; distinguish the 62B 795B-token reporting checkpoint from the 780B-token corpus and 8B/540B checkpoints; remove undisclosed PaLM 2 size and token estimates; bound architecture, benchmark, safety, derivative, product, and API claims.
- Autonomous drivingeditorial
reconstruct the article around feature-specific automation levels, operating boundaries and fallback, system architecture, lifecycle safety assurance, evidence interpretation, incidents, and current regulation; remove unsupported forecasts, driver-assistance/ADS confusion, and vendor-centric claims.
- Tensor Processing Unit (TPU)editorial
Replaces unsupported pricing and comparison claims, corrects TPU generation status and specifications through July 28, 2026, distinguishes chips, slices, pods, and Edge TPU, and adds primary and academic citations.
- Supervised Learningeditorial
Reworked supervised learning coverage with scoped definitions, leakage-safe evaluation, calibrated metrics, and documented failure modes
reconstruct CLIP from primary sources; correct model-specific text-tower widths, heads, and 49,408-token vocabulary; distinguish the 77-token context; tighten evaluation, limitations, downstream uses, and reproducibility.
- Llama 2editorial
rebuild the article around primary technical records, correct the architecture and full carbon-accounting table, distinguish released checkpoints from the withheld 34B models, and replace unsupported influence and deployment claims with bounded evaluations.
- Artificial General Intelligenceeditorial
rebuilt Artificial General Intelligence from primary and peer-reviewed sources; separated proposed definitions from consensus, bounded current capabilities and forecasts, and removed unsupported fast-aging claims
- Tool useeditorial
rebuilt Tool use from primary research and official specifications; corrected execution architecture, MCP governance, OWASP numbering, and tau-bench claims; removed duplicated and unstable score tables
- Productivityeditorial
replaced unsupported product-market claims with primary evidence, corrected study statistics, and distinguished task, firm, and economy-wide productivity
- DALL-Eeditorial
reverify the DALL-E family, replace an unsupported DALL-E 2 component total and nonexistent DALL-E 3 accuracy figure, remove unstable product claims, and rebuild the article around primary papers, dated official records, and independent academic audits.
- Question answeringeditorial
independently fact-check Question answering, correct the LUNAR result, replace unsupported claims, add 35 explicit primary or academic references, and validate canonical internal links.
- SWE-bencheditorial
replace speculative SWE-bench material with verified protocol, variants, and audit evidence
- MIT Licenseeditorial
independently verify MIT License history, terms, compatibility, adoption evidence, and AI scope
- Cursor (code editor)editorial
independently reverify Cursor features, security, current product scope, and academic citations
- ResNeteditorial
rebuilt the ResNet article from primary papers and official documentation; corrected the ImageNet evaluation table, the earlier human-reference chronology, the COCO baseline AP values, the original training duration, the ResNet-RS 83.4% model identity, and modern v1/v1.5/v2 distinctions.
- Softmaxeditorial
independently revalidated Softmax and corrected temperature/filter ordering, made the PyTorch axis wording version-robust, and clarified additive logit identifiability; rechecked all claims, citations, equations, sources, links, tables, and revision history.
- DistilGPT2editorial
Replaces the false GPT-2 redirect with a sourced DistilGPT2 article that establishes its distinct identity, reconciles parameter and evaluation labels, and documents architecture, distillation, training data, use, and limitations.
- GitHub Copiloteditorial
reverify GitHub Copilot features, billing, data terms, research, and litigation
- GPT-2editorial
Rebuilds GPT-2 as the four-checkpoint 2019 OpenAI model family; reconciles corrected parameter names, distinguishes no-fine-tuning evaluations from demonstration-free prompting, qualifies benchmarks and detection, documents WebText and staged-release limits, and adds primary and peer-reviewed evidence on bias, toxicity, memorization, privacy, distribution, and legacy.
- Llama 3editorial
separated the April 2024 Llama 3 checkpoints from later releases, replaced unsupported chronology and evaluative wording with source-bounded facts, corrected launch-era training and license scope, and rebuilt continuous citations with complete PDF evidence.
- GPTeditorial
removed speculative GPT-4-and-later architecture and parameter claims, corrected GPT-3 training-token and GPT-5 context figures, updated the release history through GPT-5.6, clarified trademark status and GPT product terminology, and rebuilt the article from primary, official, academic, procedural, and security sources.
- Object detectioneditorial
reverify Object detection, replace unsupported market and cross-hardware benchmark claims, correct dataset and detector specifications, and add deterministic primary-source citations and canonical internal links.
- DeepSeek-R1editorial
Corrects the R1 training-cost attribution and R1-Zero benchmark endpoint; rebuilds architecture, training, evaluation, licensing, update, safety, and impact coverage with protocol-specific citations and clear open-weight and hosted-service distinctions.
- Embeddingseditorial
rebuild the Embeddings article from primary research, distinguish lookup, contextual, sentence, multimodal, graph, multi-vector, and hosted API representations, remove unsupported performance and cost claims, and add dated official interface facts, compatibility rules, evaluation guidance, privacy evidence, and complete citations.
- Sam Altmaneditorial
Rebuilt the biography from primary records and authoritative reporting; corrected the false 2025 OpenAI-equity claim, qualified financing and Stargate plans, removed volatile wealth claims, and clarified procedural legal outcomes.
- Inferenceeditorial
narrowed the page to trained-model execution, removed unsupported forecasts and vendor comparisons, and added primary-source coverage of serving, LLM inference, optimization, benchmarking, and monitoring.
- Reasoning modelseditorial
reverified Reasoning models with bounded terminology, historical precursors, disclosed training and inference methods, protocol-aware evaluation, and qualified limitations; replaced unsupported chronology and cross-model rankings with 13 primary and academic sources.
- Claude Codeeditorial
replaces a bloated and stale product account with a current, date-bounded description of Claude Code's interfaces, licensing, installation, plans, security controls, data handling, release history, and research evidence, while removing unsupported market and performance claims.
- Chain-of-Thoughteditorial
fixed mixed-condition benchmark values, separated prompted CoT from trained reasoning, qualified scale, theorem, faithfulness, and monitorability claims, removed unsupported product and application claims, and rebuilt citations from primary research.
- Backpropagationeditorial
reverify Backpropagation with corrected reverse-mode, layered-network, BPTT, clipping, cost, memory, framework, biological-scope, and historical claims; normalize citations and canonical internal links.
- Regularizationeditorial
replace oversimplified and prescriptive claims with sourced definitions of explicit, Bayesian, algorithmic, data-based, and neural-network regularization; correct penalty scaling, Laplace-prior, dropout, early-stopping, weight-decay, label-smoothing, spectral-normalization, BatchNorm, and evaluation claims.
- vLLMeditorial
replace volatile promotional, adoption, funding, release-timeline, and universal benchmark claims with a primary-source account of vLLM's scope, PagedAttention, V1 architecture, interfaces, execution features, deployment, evaluation, security, and limitations; align the platform, preemption, and shared-memory wording with the exact v0.26.0 documentation.
- Scikit-learneditorial
replace volatile popularity, funding, adoption, comparison, and release claims with a July 28, 2026 version-scoped account of Scikit-learn's history, estimator API, workflows, evaluation, computing, persistence, governance, and documented limitations.
- Gradient Descenteditorial
rebuild Gradient Descent with assumption-bounded convergence results, renderer-safe formulas, exact distinctions among deterministic, stochastic, accelerated, and adaptive methods, and fully mapped primary and academic citations; explicitly distinguish Nesterov acceleration from basic gradient descent in the convergence table.
- CUDAeditorial
replaced outdated release, universal AI and speedup claims, and conflated hardware material with a primary-source account of CUDA's model, memory, toolchain, libraries, compatibility, licensing, and portability. Correct the PyTorch CUDA Semantics source-update date to the official July 17, 2026 record.
- Graphics processing uniteditorial
replace volatile pricing, roadmaps, comparison tables, and universal performance claims with a primary-source account of GPU architecture, programming, AI workloads, measurement, distributed scaling, and limitations. Correct the Owens survey record, state the Volta Tensor Core operation precisely, and identify the peer-reviewed Megatron-LM and ZeRO versions of record.
- Data Centereditorial
Replace speculative project and operator catalogs with a standards-based Data Center article; correct the Tier availability mapping; distinguish measured load from capacity and projections; document PUE, WUE, AI rack-density, reliability, grid, water, security, and reporting boundaries using primary and academic sources. Correct a misattributed DieHard reference and limit its claim to the paper's 2016 correlated power/network failure-domain study.
- Training Seteditorial
rebuilt the article around functional dataset roles, defensible splitting, leakage control, quality, representation, foundation-model corpora, privacy, security, governance, and reproducibility; removed arbitrary ratios and volatile legal claims.
- Prompt Engineeringeditorial
replace duplicated and weakly sourced material with a research-grounded account of prompt design, evaluation, reasoning methods, limitations, security, multimodal use, and context engineering; qualify inconclusive self-enhancement evidence.
- Benchmark (AI)editorial
replace unsupported and volatile benchmark claims with source-bounded guidance; remove contradictory BetterBench counts, qualify LLM-judge self-enhancement evidence, correct GAIA and Tau-bench publication records, and add construct-validity, uncertainty, contamination, resilience, and agent-evaluation coverage.
- Perplexityeditorial
distinguish the perplexity metric from Perplexity AI; repair the metric's bounds, tokenization, context-window, pseudo-perplexity, speech, topic-model, scoring-rule, and AI-detection claims; replace unsupported company figures and volatile product assertions with dated primary-source or explicitly attributed evidence.
- NeurIPSeditorial
replace unreliable prominence, paper-history, attendance, oral-count, acceptance-rate, review-consistency, and future-impact claims with edition-specific primary evidence; distinguish main, Datasets and Benchmarks, and Position Paper tracks; add the AI Events category.
- Loss Functioneditorial
distinguish loss, risk, objective, regularization, and metrics; repair equations and optimization claims; replace unsupported examples with source-bound coverage.
- Overfittingeditorial
replace categorical train-test-gap, sample-size, parameter-count, regularization, double-descent, benign-overfitting, and grokking claims with a source-scoped treatment of empirical risk, valid evaluation, leakage, shift, and modern interpolation.
- Tesla (robotics)editorial
refocus Tesla (robotics) on the verified Optimus program, distinguish demonstrations from autonomous operation and designed capacity from production, and remove unsupported FSD, pricing, deployment, and Gen 3 claims.
- LiDAReditorial
replace promotional and unsupported market claims with source-backed coverage of lidar physics, architectures, calibration, processing, applications, standards, safety, history, and documented limitations.