Discover the Best AI Resources
Curated essentials, no noise — just what matters
Lets vision-language models control robots via a compact semantic action interface that maps intent to discrete action units; supports zero-shot use of closed-source VLMs, low-cost fine-tuning of open VLMs, and GUI-based demonstration collection.
Translates natural-language instructions into executable programs that maintain an explicit, persistent global world state and compiles state-augmented 3D oriented bounding boxes into pixel-aligned conditioning signals for pretrained video generators. The approach decouples state evolution from rendering, enabling programmable entity control, off-screen state, and long-horizon interactive scenarios.
Generates full songs from lyrics and a style prompt, producing vocals and accompaniment and exporting editable symbolic scores for melody/chord control. Uses symbolic planning with agentic multi-turn editing and runs local 48 kHz inference on a 24GB GPU.
Provides low-latency, true-streaming automatic speech recognition that emits append-only committed transcripts to avoid partial-result rollbacks. Supports configurable decoding chunks (80 ms–2 s), optimized for Chinese and English, and offers vLLM and transformers backends for real-time deployment.
Snapshot delivery of arXiv metadata, submission files and rendered documents in multiple Parquet configs (metadata, paper_text, latex, source, pdf, ps). Includes ~3.15M papers, full-text TeX assemblies and indexes to fetch large assets for training, retrieval and analysis.
Suppresses grid-like and granular “digital ripple” artifacts introduced by iterative reference-conditioned image editing using selective spectral notching, structure-aware smoothing, and cleaned-reference regeneration. Prioritizes low-distortion filtering when artifacts are spectrally separable and visual reconstruction when artifacts overlap content.
A multimodal Mixture-of-Experts foundation model with a million-token context window; uses a causal encoder–decoder layout and aggressive KV-cache compression (~890 bytes/token) to limit per-token activation to 8B/16B—designed for long-context, agentic, and multimodal workloads.
Simulation-ready home dataset for embodied AI: CAD-based household scenes with configured physical properties and metadata, plus 1,000 robot trajectory episodes (RGB-D, HDF5/USDZ) for simulation training and evaluation under CC BY-NC-SA 4.0.
Defines recursive self-improvement (RSI) with an evaluation metric (Headroom-Closed Index) and a five-level autonomy roadmap—from executing human-specified improvements to recursively improving improvement mechanisms—while analyzing scenarios, verification challenges, and governance risks.
An 8B native unified multimodal model that understands, reasons about, and generates high-fidelity visual content without a separate visual encoder or VAE—focused on spatially coherent patch reconstruction, native 4K generation, multi-expert distillation, and improved text rendering and image editing.
Progressively prunes and distills audio encoders for speech LLMs to cut inference cost while preserving decoder-facing embeddings, using behavioral probes, representation alignment, cross-scale distillation and LoRA finetuning; reports reduced macro-error on Chinese–English benchmarks.
Provides a drop-in checkpoint of DeepSeek-V4.1-Flash with weight-level abliteration that removes safety guardrails to produce uncensored outputs; preserves vision, MoE routing, 1M-token context and native FP8 quantization. Intended for advanced self-hosted deployment; requires large NVLink GPU domains and careful serving setup.