AI Model2026
Generates high-fidelity 3D assets from a single image by back-projecting pixel-aligned features into 3D, preserving fine geometry and PBR textures; includes inference code and a Hugging Face demo—best suited for single-view object reconstruction.
AI Dataset2026
Provides the dataset and accompanying technical report for a DeepSeek project that interleaves spatial markers (points and boxes) into multimodal LLM reasoning. Includes a public subset of data and benchmarks under an MIT license; model weights are not included.
AI Model2026
Draft model for speculative decoding that uses a lightweight block-diffusion drafter to propose multiple tokens in parallel; designed to pair with google/gemma-4-31B-it and accelerate autoregressive text generation (official benchmarks report up to ~5.8× throughput).
AI Model2026
Transforms pretrained latent-diffusion priors into pixel-space diffusion models by removing the VAE and training shallow pixel layers on LDM-generated synthetic images — enabling fast convergence, native 4K output, and low-data training on 8 GPUs.
AI Dataset2026
Provides paired images and English captions for vision–language research, curated by Stanford Vision Lab and hosted on Hugging Face; useful for training and evaluating multimodal models and reproducing related research.
AI Dataset2026
Provides a county-harmonized corpus of U.S. municipal and county ordinance text (≈2.21M chunks) labeled for function, substantive indicator, and topic to support legal NLP, retrieval, and comparative local-law research. Includes model-assigned labels and continuous scorers (opacity, paternalism, enforcement discretion) plus coverage metadata; not exhaustive or a substitute for legal advice.
Preview of an MoE model family (V4-Pro: 1.6T params, 49B active; V4-Flash: 284B, 13B active) built for 1M-token contexts. A hybrid attention design cuts single-token inference FLOPs to 27% and KV cache to 10% versus V3.2 at million-token length.
AI Dataset2026
Provides a curriculum-aligned knowledge graph extracted from Chinese K–12 textbooks and accompanying benchmarks and training data to evaluate and train educational LLMs. Releases a 23,640-question multi-select benchmark and a 7,335-sample graph-guided training corpus with multimodal VQA pairs and the full construction pipeline.
AI Dataset2026
Multilingual benchmark for evaluating LLMs' industrial domain knowledge via 2,049 expert-curated QA pairs spanning 10 product verticals and four languages, with each item grounded to industry or national standards and an LLM-as-judge evaluation pipeline.
AI Dataset2026
Transfers pretrained latent diffusion priors into pixel space to train pixel-space diffusion models using only synthetic images from LDMs. Trains shallow pixel layers while freezing most LDM internals, reducing data and compute needs and enabling native 4K generation without a VAE.
AI Dataset2026
RL training dataset for long-context language-model fine-tuning with ~23K samples and nine reward types, provided in Parquet with bilingual ground-truth and reward metadata for direct RL/bench evaluation.
AI Dataset2026
Provides 100,000 generated low-quality↔high-quality image pairs created with modern multi-frame/multi-modal models to boost generalization of image restoration methods; includes train/test JSONL lists, baseline training code, and pretrained checkpoints under CC BY‑NC‑ND 4.0.