AI Dataset2026
Provides an annotated multimodal human-motion dataset for language-to-action and robotics research, with BVH and MuJoCo files plus recordings targeted at Unitree-G1 and NVIDIA-SOMA platforms. Covers locomotion, gestures, dance and object interaction with English annotations and 100K–1M samples.
AI Model2026
Generate text, images, video, audio and action/robot trajectories from combined text, image, video, audio and action inputs. A Mixture-of-Transformers omnimodal foundation model (Cosmos3‑Nano, 16B params) focused on Physical AI (robotics, AV, simulation) and optimized for NVIDIA GPU runtimes.
AI Model2026
Instruction-tuned Gemma 4 31B multimodal model that generates text from text+image inputs with up to 256K context. Dense 31B variant optimized for vision-language understanding, long-context reasoning, and coding; Apache‑2.0 licensed.
AI Dataset2026
JSONL dataset of Claude Opus 4.6 chain-of-thought traces paired with high-difficulty math and logic problems for supervised fine-tuning and distillation; exposes step-by-step reasoning to teach process-oriented problem solving and improve math/logic accuracy in smaller LLMs.
AI Dataset2026
Provides 10 million synchronized egocentric experience episodes with structured 3D/4D multimodal annotations — 2.88B RGB frames, 720M depth frames, 576M pose/mocap frames and ~1PB total. Designed for embodied AI, robotics, and multimodal pretraining; research-only, gated access.
AI Model2026
Instruction-tuned Mixture-of-Experts multimodal model that generates text from text+image inputs while activating a 4B subset of parameters for faster inference; supports a 256K context window, multilingual vision-language tasks, and is available under Apache-2.0.
AI Dataset2026
Provides a 1,000-row sample user–item interaction Parquet for the TAAC2026 recommendation task, using a flat column layout with 120 top-level columns (IDs, labels, user/item int & dense features, and four-domain behavioral sequences). Updated 2026-04-10.
AI Agent2026
Turns a single research idea into runnable experiments and a conference-ready paper by orchestrating an LLM-driven end-to-end workflow (literature → design → code → sandboxed runs → analysis → writing). Provides human-in-the-loop checkpoints, domain-specialist executors, and multi-layer citation verification.
AI Model2026
A distilled 26M-parameter encoder–decoder LLM for on-device function-calling and tool use. Uses a pure-attention Simple Attention Network, provides open weights and local finetuning, and targets high-throughput inference on the Cactus runtime.
AI Model2026
Pretrained image-model checkpoint hosted on Hugging Face by Facebook (Meta) for vision experiments and transfer learning. Includes downloadable weights and metadata under CC BY‑NC 4.0 — suitable for research and prototyping but restricted for commercial use.
AI Dataset2026
A 228,557-example dataset of reasoning traces segmented into blocks with iterative, compressed "memento" summaries so LLMs can learn to manage long context. Includes a training-ready subset and a `full` subset with sentence/block-level annotations for research and SFT.
AI Dataset2026
Large-scale mid-training corpora for multimodal models: 10,809 ~60s video shards, caption splits (30s/60s/180s/>10min), 84 spatial-reasoning shards, and CSV mappings to source YouTube IDs. Small Parquet preview configs are provided for schema inspection.