AI Model2026
Runs a full 27B-class language model using end-to-end binary (1.125-bit) weights, cutting FP16 size to ~3.9 GB. Key features: 262k-token context, custom 1-bit kernels for Apple MLX and CUDA, and an optional DSpark drafter for faster decoding. Best when memory footprint matters; trades some FP16 accuracy for on-device feasibility.
AI Model2026
Runs a full 27B-class Qwen3.6-derived language model in a ~3.9 GB 1-bit GGUF pack for on-device inference with a 262K-token context; true 1.125 bits/weight binary representation, DSpark speculative drafter, and llama.cpp (CUDA/Metal/CPU) support.
AI Model2026
Runs a full 27B-class Qwen3.6-derived LLM in a ~7.2 GB ternary/2‑bit format for on-device or single‑GPU text generation, retaining ~95% of FP16 performance and supporting a 262K‑token context. Designed for laptop/GPU deployment; exceeds typical phone memory limits.
AI Dataset2026
Provides structured egocentric manipulation signals from smartphone videos: MANO 3D hand reconstructions, metric camera trajectories, and fine-grained atomic action segments (full release ≈2,000 hours planned). Supplies aligned hands.npz, camera_traj.npz, undistorted intrinsics and segment annotations for embodied-learning pipelines.
Continuously records egocentric visual and audio streams into a lightweight streaming memory that organizes experiences into current, short-term, and long-term tiers and retrieves multimodal evidence to answer queries about past events. Built for on-device use (smartphones/AI glasses) with dynamic retrieval routing.
AI Agent Papers2026
Designs and evaluates a foundation GUI agent that performs cross-platform GUI and CLI actions on real devices to complete long-horizon workflows. Emphasizes a unified action space, a large-scale real-device mobile runtime, an AutoResearch-style data flywheel, and online RL training across 10,000+ concurrent environments.
AI Model2026
Multimodal vision-language model optimized for on-device image+text tasks: image captioning, full-page OCR with layout annotation, grounding/bounding-box prediction, and function calling. Built on the LFM2.5-2.6B backbone with a SigLIP2 NaFlex 400M vision encoder and tuned for low-latency, low-memory edge inference.
AI Dataset2026
Provides a year-scale multimodal benchmark and evaluation framework for on-device long-term memory in personal assistants, built from real mobile user trajectories. Tests memory construction, retrieval, updating, temporal reasoning, and implicit preference inference, and includes a knowledge-grounded synthesis pipeline to form coherent long-horizon trajectories.
AI Model2026
A 9B open-weight reasoning LLM that uses a self-improvement loop to auto-generate tasks, construct scaffolds, and optimize rollouts for stronger agentic coding and long-context reasoning. Single-GPU deployable, supports tool-calling and a 262,144-token context window.
AI Agent Papers2026
Assesses mobile planning agents' ability to call tools, plan long-horizon workflows, and coordinate sub-agents in realistic, interactive phone scenarios via a stateful executable sandbox. Covers 13 domains, 212 tools, evidence-based verification, and tests memory, skill usage, permission and runtime constraints.