dataset
30 articles about dataset in AI news
Donate Claude Code Traces to Hugging Face's Open Dataset in One Command
Trace Commons lets Claude Code users donate anonymized session traces to an open CC-BY-4.0 dataset on Hugging Face. Run `/donate-trace` after open-source work to share how you solved problems — without exposing secrets or paths.
AllenAI's MolmoAct2: 720-Hour Bimanual Dataset, Beats GPT-5 on Robotics
AllenAI released MolmoAct2, an open robotics model with a 720-hour bimanual dataset, beating GPT-5 and Gemini Robotics on success rate (89.4% vs 82.1%) with 40% lower latency.
Apple Releases DFNDR-12M Dataset, Claims 5x CLIP Training Efficiency
Apple has open-sourced DFNDR-12M, a multimodal dataset of 12.8 million image-text pairs with synthetic captions and pre-computed embeddings. The company claims it enables up to 5x training efficiency over standard CLIP datasets.
Tencent Releases MegaStyle: 1.4M AI-Generated Image Style Dataset
Tencent has open-sourced MegaStyle, a 1.4 million image dataset for style transfer and text-to-image fine-tuning. It was generated by systematically pairing 170,000 style prompts with 400,000 content prompts using the Qwen-Image model.
FashionStylist: New Expert-Annotated Dataset Aims to Unify Multimodal
A new arXiv preprint introduces FashionStylist, a dataset with professional fashion annotations for item grounding, outfit completion, and outfit evaluation. It aims to address the fragmentation in existing fashion AI benchmarks by providing expert-level reasoning data.
Massive Video Reasoning Dataset Released, Reportedly 1000x Larger Than Predecessors
An unverified report claims the release of a video reasoning dataset roughly 1000x larger than existing benchmarks. If true, it would be a significant resource for training next-generation video understanding models.
Tencent Launches 2025 Ad Algorithm Challenge with Massive All-Modality Recommendation Datasets
Tencent has launched an open competition and released two industrial-scale datasets (TencentGR-1M and TencentGR-10M) to advance generative recommender systems. This has spurred related research into debiasing techniques and novel reranking frameworks, moving the field toward more holistic, multi-modal user modeling.
QUMPHY Project's D4 Report Establishes Six Benchmark Problems and Datasets for ML on PPG Signals
A new report from the EU-funded QUMPHY project establishes six benchmark problems and associated datasets for evaluating machine and deep learning methods on photoplethysmography (PPG) signals. This standardization effort is a foundational step for quantifying uncertainty in medical AI applications.
Unitree Robotics Releases UnifoLM-WBT-Dataset: A Large-Scale, Real-World Robotics Dataset for Embodied AI
Chinese robotics firm Unitree Robotics has open-sourced the UnifoLM-WBT-Dataset, a high-quality dataset derived from real-world robot operations. The release aims to accelerate training for embodied AI and large language models applied to physical systems.
DIET: A New Framework for Continually Distilling Streaming Datasets in Recommender Systems
Researchers propose DIET, a framework for streaming dataset distillation in recommender systems. It maintains a compact, evolving dataset (1-2% of original size) that preserves training-critical signals, reducing model iteration costs by up to 60x while maintaining performance trends.
Niantic's Pokémon GO Dataset of 30B Images Now Powers Centimeter-Precise Robotics Vision
Niantic's Lightship VPS, trained on 30 billion images from Pokémon GO players, now enables delivery robots to navigate with centimeter precision. The dataset represents the largest real-world visual positioning system ever created.
Massive Open-Source Dataset of Computer Screen Recordings Released to Train AI Agents
Researchers have released the world's largest open-source dataset of computer-use recordings on Hugging Face. The collection contains 48,478 screen recording videos totaling approximately 12,300 hours of professional software usage, licensed under CC-BY-4.0 for AI training and evaluation.
OpenAI's IH-Challenge Dataset: Teaching AI to Distinguish Trusted from Untrusted Instructions
OpenAI has released IH-Challenge, a novel training dataset designed to teach AI models to prioritize trusted instructions over untrusted ones. Early results indicate significant improvements in security and defenses against prompt injection attacks, marking a step toward more reliable and controllable AI systems.
HumanMCP Dataset Closes Critical Gap in AI Tool Evaluation
Researchers introduce HumanMCP, the first large-scale dataset featuring realistic, human-like queries for evaluating how AI systems retrieve and use tools from MCP servers. This addresses a critical limitation in current benchmarks that fail to represent real-world user interactions.
DeepVision-103K: The Math Dataset That Could Revolutionize AI's Visual Reasoning
Researchers have introduced DeepVision-103K, a comprehensive mathematical dataset with 103,000 verifiable visual instances designed to train multimodal AI models. Covering K-12 topics from geometry to statistics, this dataset addresses critical gaps in AI's visual reasoning capabilities.
DeepVision-103K: The Math Dataset That Could Revolutionize How AI 'Sees' and Reasons
Researchers have introduced DeepVision-103K, a massive dataset designed to train AI models to solve math problems by understanding both text and images. This approach could significantly improve how AI systems reason about the visual world.
A Reference Architecture for Agentic Hybrid Retrieval in Dataset Search
A new research paper presents a reference architecture for 'agentic hybrid retrieval' that orchestrates BM25, dense embeddings, and LLM agents to handle underspecified queries against sparse metadata. It introduces offline metadata augmentation and analyzes two architectural styles for quality attributes like governance and performance.
FedAgain: Dual-Trust Federated Learning Boosts Kidney Stone ID Accuracy to 94.7% on MyStone Dataset
Researchers propose FedAgain, a trust-based federated learning framework that dynamically weights client contributions using benchmark reliability and model divergence. It achieves 94.7% accuracy on kidney stone identification while maintaining robustness against corrupted data from multiple hospitals.
Function-Aware Fill-in-the-Middle Boosts SWE-Bench by +5.4 on 14B Models
Function-aware FIM mid-training boosts SWE-Bench by +2.8 to +5.4 on 7B-14B models, preserving general abilities. Six checkpoints and 400K dataset open-sourced.
Rich Sutton Launches Oak Lab to Build Self-Learning AI Agents
Rich Sutton founded Oak Lab to build self-learning AI agents. He rejects static datasets for real-time reinforcement learning with a trillion-parameter goal at 20W.
AWS launches MCP server for its open-data registry
AWS launched an MCP server for its Registry of Open Data, giving AI agents natural-language access to 170+ public datasets.
SingGuard: Runtime Guardrails for Multimodal AI Treat Safety as Input
SingGuard treats safety rules as runtime inputs for multimodal AI, achieving SOTA across 6 families and 35 datasets via fast/slow reasoning.
How Simon Willison Ported a 0.2B Image Model to the Browser with Claude
Simon Willison used Claude Code to port a 0.2B image inpainting model to WebGPU, running it as a parallel side project while his main agent worked on Datasette. The technique? Research with Claude.ai, then hand off to Claude Code with research.md.
LOCUS-v1: 2.2M US Laws Hit HuggingFace via AI Pipeline
LOCUS-v1, a dataset of 2.2M US laws built via AI pipeline, released on HuggingFace. First comprehensive legal database of its kind, but quality and validation metrics remain undisclosed.
How to Build Claude Code Tools That Ask Users Questions Mid-Execution
Datasette Agent 0.2a0's `context.ask_user()` lets tools pause for user input mid-execution. Claude Code users can adopt this pattern for safer, more interactive tool workflows.
SpatialBench: New Benchmark Tests Foundation Models on 3D Tasks
SpatialBench, a new benchmark from ropedia_ai, evaluates spatial foundation models across 7 tasks and 5 datasets, testing depth estimation, surface normal prediction, and 3D object detection.
Federated Fine-Tuning Benchmark Shows QLoRA Nears Centralized Accuracy on
Sherpa.ai's arXiv benchmark shows federated fine-tuning with QLoRA matches centralized accuracy on four healthcare and finance datasets, outperforming isolated single-institution learning under non-IID conditions.
LASAR Cuts Latent Reasoning Steps in Half for GenRec at 20x Speedup Over CoT
LASAR nearly halves latent reasoning steps and achieves 20x speedup over explicit CoT in generative recommendation, outperforming baselines on three datasets.
Simple Graph Heuristic Beats Generative Recommenders on 10 of 14 Benchmarks
A no-training graph heuristic beats generative recommenders on 10 of 14 benchmarks, exposing shortcut-solvable datasets. Relative NDCG@10 gains hit 44% on Amazon CDs.
OpenAI Privacy Filter Gets 6x More PII Labels via Nvidia Data
OpenAI has retrained its privacy filter using Nvidia's Nemotron-PII dataset, expanding PII detection from 8 to over 50 label types, targeting healthcare and enterprise use cases with better accuracy.