Frames AI research as a trainable practice of reading, building, debugging, and fast feedback. The essay is most useful for researchers learning how to avoid hype-chasing, benchmark tunnel vision, and agent-induced blind spots.
Converts large-scale egocentric human videos into robot-format pseudo-action trajectories and introduces ACE-EGO-0, a VLA pretraining framework that unifies camera-space actions, morphology conditioning, and reliability-aware weighting to jointly learn from noisy human and high-quality robot data for improved robotic manipulation transfer.
AI Dataset2026
Provides 130k+ bimanual teleoperation trajectories for robot imitation learning, recorded on low-cost YAM two-arm rigs and shared as MCAP episodes with subtask annotations, training code, and checkpoints.
AI Dataset2026
Provides pre-parsed arXiv LaTeX source files aligned with official metadata as ready-to-query Parquet rows. Bundles each paper's .tex/.bib/.sty etc. into a single readable tree, updates monthly, and simplifies large-scale access for LLM pretraining, document understanding, and citation analysis while requiring adherence to original arXiv licenses.
AI Dataset2026
Provides 319 newline-delimited JSON agent session traces captured from GLM-5.2 using Teich for training agentic models. Preserves reasoning-first assistant fragments, tool-call events, and a dataset-level training-ready tool schema; convertible to OpenAI-style JSONL for SFT/distillation.
AI Dataset2026
Provides agentic instruction‑tuning trajectories for software‑engineering tasks, formatted for supervised fine‑tuning and agent training. Contains multi‑file edits, tests, docs and structured agent traces (≈5,115 records, 1.9 GiB). Intended for commercial use; licensed CC‑BY 4.0 with additional permissive licenses.
AI Dataset2026
Zeren Jiang, Yushi Lan +9Visual Geometry Group, University of Oxford, Nanyang Technological University +1
Provides multiview synthetic RGB video clips with per-frame depth, instance masks, dense long-range 3D point tracks, camera poses, and SMPL‑X human pose/shape labels for 4D reconstruction, tracking, and geometry-aware novel-view synthesis. Includes ~4.7K clips (1.4M frames) and is licensed for AI training.
AI Dataset2026
Provides 600,000+ first-person player-round videos (10,000+ hours) with per-frame keyboard, mouse-delta, and 3D trajectory annotations in WebDataset shards—built for training world models, action-conditioned video, and imitation-learning workflows (non-commercial license).
AI Image2026
Provides 1,503 Krea 2 style LoRAs (original safetensors + ComfyUI builds) trained on fal.ai, each with a short trigger phrase and downloadable weights for quick style transfer or further retraining.
AI Model2026
Mixture-of-Experts LLM designed for million-token contexts, combining hybrid compressed attention, FP4/FP8 quantization-aware training for MoE experts, and multi-mode 'thinking' (Non-think/Think High/Think Max); includes a speculative-decoding extension for faster inference.
Proposes Monotonic Inference Policy Improvement (MIPI) and a two-step Monotonic Inference Policy Update (MIPU) to address training–inference probability mismatch in LLM reinforcement learning by constructing sampler-referenced candidate updates and accepting synchronized updates using an inference-gap proxy; shows improved reasoning accuracy and stability under FP8-quantized rollouts.
AI Model2026
A large-scale MoE language model for agentic coding and long-context tasks, natively supporting 1M-token context and dynamically activating tens of billions of parameters per token. Uses sparse attention and zero-computation experts to allocate compute per-token; model weights planned for release.