Discover the Best AI Resources
Curated essentials, no noise — just what matters
Generates synchronized spoken dialogue and explicit full-body co-speech motion (facial expressions, hands, upper- and lower-body) end-to-end from the same hidden states, replacing the speech-then-motion cascade. Trains with a scalable pseudo-labeling pipeline (422,856 ranked pairs) and supports real-time inference (RTF 0.78) while matching teacher motion metrics within ~2%.
AI Dataset2026
Provides a unified, camera-conditioned, multi-source video dataset and reproducible processing pipeline for training long-horizon video world models. Key features: a canonical frame-aligned contract (visuals, camera geometry, captions, quality metadata), 1.43M canonical clips with portable releases and reconstruction tools; large download and some backbone assets carry separate licenses.
AI Agent Papers2026
Trains LLM agents to proactively edit and manage their working context for long-horizon tasks using an expanded toolset (planning, long-term memory, soft offloading) and a fine-grained RL algorithm that identifies critical edits and assigns action-level credit. Improves accuracy while keeping contexts compact on long-context QA and deep search.
AI Model2026
Provides per-tensor non-uniform GGUF quantizations of Qwen3.8-27B using GSQ and RCO, delivering high accuracy at 2.5–3.5 bits and including a BF16 vision projector for multimodal use. Optimized to run unmodified in llama.cpp, Ollama, and LM Studio.
Proposes GenFirst, a generation-before-reconstruction end-to-end training strategy for latent generative models that avoids latent collapse by prioritizing generative objectives and then progressively strengthening reconstruction, validated with strong gFID/GenEval results on ImageNet-256 and text-to-image tasks.
AI Model2026
Drop-in abliterated (refusal-removed) build of GLM-5.3-Flash that bakes refusal-direction removal into block-FP8 safetensors, yielding an uncensored 320B (18B active) multimodal MoE model with a 1M-token context. Intended for red-teaming, interpretability, and robustness research; MIT license; not for production without added guardrails.
AI Model2026
Provides a cybersecurity-focused CRACK variant of GLM-5.3 FP8 that reduces refusals for offensive-security, red-team, exploit-development and malware-analysis queries while retaining native FP8 speed on Hopper GPUs; MIT-licensed for authorized security work.
AI Dataset2026
Synthesizes 234K self-contained, high-difficulty scientific reasoning QA pairs by distilling research papers into compact 'reasoning skeletons'. Emphasizes mechanistic reasoning, hypothesis falsification, quantitative derivation and boundary calibration; built for SFT and reasoning evaluation.
AI Dataset2026
Provides image-level tag correction instructions for a Danbooru anime-image tagging corpus, listing per-post tags to add or remove. Contains 1.74M normalized correction rows (snapshot 2026-08-30); it's a corrections manifest (no images) intended to be applied to existing metadata.
AI Video Papers2026
Generates synchronized native 2K audio-video from a single first frame and a text prompt using a compact 7B joint generator. Combines gated cross-modal attention, progressive joint training, audio-video reinforcement learning, and an Autoregressive 1-Step 2K Refinement; releases a 7B generator and 2K Refiner for research use.
AI Dataset2026
Provides 997 chain-of-thought cybersecurity reasoning records distilled from the Kimi K3 model, each with an explicit <think> trace and a technical resolution or structured tool invocation. Includes verified tool-call objects, diffs, cross-domain coverage, and token-level metadata for fine-tuning and evaluating reasoning models.
AI Dataset2026
A living, crowdsourced dataset of hard-to-translate examples (text, images, audio, video) paired with handcrafted verification rules that flag concrete MT failures. LTBv1 contains 3,456 peer-reviewed examples across many language pairs and accepts ongoing contributions.