AI Video2026
Generates short videos that preserve a reference person's identity from a single reference image as a LoRA adapter for LTX-2. Uses overlap reference conditioning with TASS‑RoPE source-phase tagging and an ArcFace identity loss; runs in ComfyUI via BFS Nodes and supports a 4‑panel character‑sheet mode for clothing/body consistency.
AI Model2026
Decides whether a user prompt should be executed locally on an edge small LLM or routed to a larger cloud model, emitting a deterministic pipe-separated decision string. A 51.7M micro-LLM fine-tuned with multi-task sequence generation to predict domain, complexity and code/math flags, optimized for ultra-low latency edge routing.
AI Dataset2026
Provides labeled prompts with full-reference answers (including chain-of-thought and code blocks) and per-example metadata to train edge routing/orchestrator models that decide whether to handle inputs locally or route them to larger models. Includes complexity scores, coding/math flags, routing justifications, and an automated override rule; suited for fine-tuning small models (50M–1.5B) for edge deployment.
AI Dataset2026
Provides re-annotated academic video instruction data for captioning, video QA, and fine-grained motion understanding; rewrites short answers and concise captions into evidence-grounded, instruction-following responses and supplies JSONL annotation files (original videos not included).
AI Agent Papers2026
Trains cross-platform GUI agents by combining a Uni-GUI cross-platform dataset with platform-conditioned multi-teacher on-policy distillation, enabling a shared policy to adapt to new platforms while retaining platform-specific behaviors; suitable for research on continual GUI agent learning and cross-platform adaptation.
AI Model2026
Fine-tuned variant of Qwen3.6-27B that cuts internal reasoning (‘thinking’) token usage by roughly 46% on average while preserving benchmark accuracy and safety behavior. Targets lower latency and inference cost; ships on Hugging Face with GGUF quantizations for local use.
AI Model2026
Deployment-optimized hybrid MoE LLM (75B total / 9.3B active) produced via Iterative Puzzle compression and Multi-Token Prediction to double server throughput and raise single-GPU concurrency; designed for multilingual reasoning, long-context generation, and high-volume agentic/chat deployments.
AI Video Papers2026
Provides a reflexive agentic framework for long-horizon video understanding that replaces costly iterative reasoning with dual contextual states: a consolidated global multimodal script and parametric latent states for fast retrieval and response, improving speed and memory efficiency.
AI Model2026
GGUF-format quantized release of DeepSeek‑V4‑Flash for local inference — compatible with llama.cpp and Unsloth runtimes, with guidance for FP4/FP8 mixed precision and Q4/Q8 quantization; tuned for million-token long-context usage.
AI Model2026
Provides pre-converted colibrì-format int4 weights so GLM-5.2 (744B MoE) can run by streaming routed experts from disk on a consumer machine with ~25 GB RAM. Includes MTP shard for lossless speculative decoding; requires the colibrì engine and ~400 GB NVMe.
AI Model2026
27B multimodal LLM post-trained to prioritize agentic, weight-scaled reasoning over 64K-token contexts. Built on Qwen3.6-27B and released with BF16 weights plus several GGUF quants; aimed at coding, long-document reasoning, tool use and multimodal inspection.
AI Model2026
Enhances KREA-2 Turbo image generations with an aesthetic LoRA trained on a curated 100-image dataset to add stronger composition, richer lighting, softer atmosphere and refined textures; trigger with --preview for art-directed, cinematic outputs in text-to-image pipelines.