Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides a unified multimodal framework for large-scale 3D understanding, text-to-3D generation, and instruction-guided 3D editing. Trains on an 87M-sample 3D multimodal corpus (25M understanding, 50M generation, 12M editing) and pairs a vision-language model with a diffusion-based 3D synthesizer to preserve structure and enable part-aware edits; suited for researchers building text-driven 3D asset pipelines but requires large compute and data.
A pretrain-then-transfer method for streaming recommendation that decouples refreshable behavioral knowledge from task-specific geometry to enable continual model refresh without downstream interference; introduces Behavioral Multi-Token Prediction and Anchored Calibration Residual and shows 4–12% offline gains plus live Shopee A/B lifts.
AI Model2026
Provides ComfyUI-ready INT8 MiniMax‑H3 checkpoints (conditioning encoder plus optional generation tail) for a Heretic-edited Qwen3‑VL‑32B source; preserves the vision tower in BF16 and uses row-wise ConvRot INT8 quantization to reduce VRAM needs for ~32GB GPUs. Not a full Transformers generation repository.
Frames skill generation as a sequential editing task and introduces a novel rollback reward to train an RL generator (Skill-α) that evaluates each edit by its downstream execution impact, producing skills that improve agent success rates across document-to-skill and experience-to-skill settings.
AI Video Papers2026
Introduces WorldExam, a diagnostic benchmark that evaluates controllable video world models across four levels from visual quality to inherent world reactivity. Covers 1,474 cases across eight tasks and supports camera-, action-, and language-driven paradigms, measuring scene-conditioned reactions beyond explicit instructions.
AI Model2026
ComfyUI-ready H3 conditioning encoder builds for Qwen3-VL-32B: a BF16 full-precision checkpoint, an INT8 ConvRot quantized checkpoint, and an optional generation tail (layers 50–63). Retains vision tower in BF16 and targets H3 workflows and lower-VRAM systems.
A continuous-latent diffusion language model that preserves a high-capacity, decodable text latent and directly models its distribution via a block-causal diffusion transformer and query-based encoder–decoder; achieves top results on OpenWebText and XSum while scaling to 1B parameters.
AI Agent Papers2026
Reformulates long-horizon agent execution as explicit task-state management: a manager defines bounded subtasks, fresh-context executors run them, and read-only auditors verify outcomes. Shows large performance gains on WeaveBench, Terminal-Bench and OSWorld.
AI Dataset2026
Installation-oriented dataset that packages ComfyUI-ready files and instructions for running MiniMax H3 locally — includes pruned/INT8/BF16 checkpoints, matching Qwen3-VL text encoders, video/audio VAEs, and official ComfyUI workflow templates for joint audio+video generation.
AI Dataset2026
Provides 37,484 validated command-line tasks generated by recursive task synthesis, each paired with searchable metadata and a sanitized, runnable package (instructions, solution, verifier, and optional Dockerfile).
Supervises audio reasoning by generating per-sample, audio-grounded rubrics that evolve with model rollouts and serve as reinforcement-learning rewards, improving perception and adaptive multi-step reasoning while avoiding reward saturation.
AI Dataset2026
Provides time-aligned simulated urban driving recordings that pair high-rate CSI/CIR with multi-view cameras, LiDAR, radar, IMU and GNSS for perception-to-channel research; contains 100 validated 1-second samples produced with CARLA and Sionna, but is limited in scene diversity and real-world fidelity.