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Hugging Face
AI Dataset·2026
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Nemotron-Personas-El-Salvador

Rodrigo Malossi, Andre Manoel +9

Provides ~1M synthetic Salvadoran‑Spanish personas (148k records, ~300M tokens) grounded in 2024 census distributions for demographics, occupations and locations; intended for training/evaluating localized LLMs and synthetic-data workflows. CC BY 4.0, adults only.

#huggingface#nvidia#nlp#multilingual#llm+2
Computer Vision Papers·2026
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VideoKR: Towards Knowledge- and Reasoning-Intensive Video Understanding

Lin Fu, Zheyuan Yang +4

Large-scale training corpus for knowledge- and reasoning-intensive video understanding: 315K video reasoning examples over 145K CC-licensed expert-domain videos, with human-in-the-loop chain-of-thought rationales to strengthen post-training for video reasoning. ([arxiv.org](https://arxiv.org/abs/2606.05259))

#video#vision#paper#multimodal#ai-train
Hugging Face
AI Model·2026
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NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16

NVIDIA Corporation

Open-weight frontier LLM for agentic reasoning and long-context analysis (up to 1M tokens). Uses a LatentMoE + Mamba-2 hybrid with Multi-Token Prediction and NVFP4 efficiency (550B total / 55B active). Suited for multilingual agents, RAG, and heavy tool-use workloads.

#nvidia#pytorch#transformers#LLM#multilingual+9
Hugging Face
AI Model·2026
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NVIDIA-Nemotron-3-Ultra-550B-A55B-NVFP4

NVIDIA

Multilingual frontier LLM optimized for long-context reasoning and agentic workflows, combining a LatentMoE (Mamba-2 + MoE) hybrid architecture with Multi-Token Prediction and NVFP4 quantization; targeted for NVIDIA GPU deployments and governed by the OpenMDW-1.1 license.

#nvidia#pytorch#transformers#LLM#multilingual+8
Hugging Face
AI Dataset·2026
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CustoMDiT / PexelsCustom-1M

carpedkm

Provides 1,036,431 identity–text–video triplets with per-video JSON annotations and reference keyframes to train and evaluate identity-preserving customized video generation models. Data is drawn from ~320K Pexels HD videos; videos must be downloaded separately per Pexels' terms.

#ai-video#video#huggingface#pandas#diffusers+1
AI Agent Papers·2026
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SearchSwarm: Towards Delegation Intelligence in Agentic LLMs for Long-Horizon Deep Research

Pu Ning, Quan Chen +8

Guides LLM-based agents to decompose long-horizon research problems and delegate subtasks to constrained subagents, then fine-tunes models on harness-generated trajectories so delegation decisions become internalized. Reports SearchSwarm-30B-A3B achieving top BrowseComp scores for its scale.

#ai-agent#agent-skills#llm#paper#ai-train+1
Hugging Face
AI Dataset·2026
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HIW-500: Humanoids In-the-Wild Dataset

BitRobot, Unitree +1

Provides 500+ hours of human whole-body teleoperation demonstrations for humanoid robot learning in real homes, with synchronized video, joint states, action traces and language annotations. Includes 23K+ episodes, fine-grained subtask labels, and raw ROS/MCAP plus compressed LeRobot formats.

#robotics#multimodal#vision#huggingface#ai-train+1
Hugging Face
AI Dataset·2026
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UltraX (openbmb/UltraX-Preview)

OpenBMB

Refines large-scale English pretraining corpora by predicting per-instance structured edits (insert, delete, replace) and deterministically applying them to produce cleaner text for LLM training. Provides five ~20B-token refined corpora in parquet with edit metadata and simple loading configs.

#llm#huggingface#nlp#polars#pytorch+1
AI Agent Papers·2026
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Toward Generalist Autonomous Research via Hypothesis-Tree Refinement

Jiajie Jin, Yuyang Hu +16

Lets an AI agent propose, run, and evaluate multi-step research experiments using a persistent Hypothesis Tree that links hypotheses, artifacts, evidence, and distilled insights. Combines a long-lived coordinator with short-lived executors to carry lessons across time; evaluated on six ML tasks.

#paper#ai-agent#agent-skills#ai-workflow#ai-train+2
Hugging Face
AI Dataset·2026
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ChingMu Robot Motion Dataset

CMRobot, Shanghai Chingmu Vision Technology Co., Ltd.

Provides 1000+ hours of high-precision optical motion-capture for humanoid robotics and embodied AI, including full-body skeleton, 20+DoF hands, object 6D, and multi-view video at 120 Hz. Sub-mm spatial accuracy, BVH/CSV/NPZ outputs and Unitree G1 retargets; ideal for imitation learning and sim-to-real, with some raw captures gated by license.

#robotics#multimodal#huggingface#ai-train#video
Hugging Face
AI Dataset·2026
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lordx64/agentic-distill-fable-5-sft

lordx64·lordx64, Glint-Research

Provides 4,659 agentic single-turn SFT training pairs extracted from Claude Fable‑5, formatted as a single-column parquet for Qwen-style fine-tuning. Includes explicit chain-of-thought (<think>) blocks, XML-serialized <tool_use> calls, PII redaction, and AGPL-3.0 licensing.

#huggingface#claude#qwen#anthropic#ai-agent+5
Hugging Face
AI Dataset·2026
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Glint-Research/Fable-5-traces

Glint-Research

A collection of 953 JSON-formatted Fable 5 interaction traces (includes chain-of-thought entries), published on Hugging Face under AGPL-3.0 — meant for fine-tuning or analyzing LLM behavior but subject to license and provenance constraints.

#huggingface#pandas#nlp#llm#ai-train+1
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