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Robótica & RL

Papers, modelos e datasets em alta no Hugging Face, além do blog oficial — com leitura editorial em português.

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Blog Robótica & RL

TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction

arXiv:2607.29231v1 Announce Type: new Abstract: Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile sensing systems that capture fine-grained fingertip interactions without compromising natural operation remains a key challenge. This reduces the reliability of human-to-robot transfer in contact-rich tasks. In this work, we present TacPrint, a wearable fingertip tactile sensor, where protrusions on ...

03.08.2026
Blog Robótica & RL

Advances, challenges, and opportunities for legged robots

arXiv:2607.28952v1 Announce Type: new Abstract: Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand their effects on society and how they can enable scientific discovery, we assess the current capabilities of these systems along hardware, locomotion, autonomy, data, and applications. We identify recent advances and key open challenges that must be overcome to enable widespread adoption and new use cas...

03.08.2026
Blog Visão Computacional

Predicting Steel Fatigue Life from Micrographs Using Physics-Informed Deep Learning

arXiv:2607.28695v1 Announce Type: new Abstract: Here is the plain text version optimized for arXiv's submission form. Custom macros (like \CV and \SI) have been converted to standard text/math so they render correctly on the webpage: Evaluating the fatigue life of structural steels conventionally requires mechanical testing lasting tens to hundreds of hours, making it impractical for rapid quality control. We present CV, a computer vision framework that estimates the fatigue life ($\log N_f$) of...

03.08.2026
Blog LLMs & Texto

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural understanding of Agentic AI, particularly in separating inference, orchestration, and execution layers for autonomous AI agents. Despite recent advances, unified frameworks for designing and evaluating full-stack agentic systems remain limited. This paper presents a comprehensive, layered architecture ...

03.08.2026
Blog Geração de Imagem

Evaluation-Verification Reward for Consistent Multi-Reference Image Editing

arXiv:2607.29025v1 Announce Type: new Abstract: While recent image editing models have made rapid progress, multi-reference editing remains challenging, particularly in maintaining visual consistency across references and ensuring overall visual harmony. Reinforcement learning has proven highly effective for text-to-image generation and single-image editing, but its extension to multi-reference editing is hindered by the absence of suitable reward models that capture multi-image relational const...

03.08.2026
Blog Robótica & RL

SCMA: Structure-Conditioned and Metal-Aware Flow Matching for CT Metal Artifact Reduction

arXiv:2607.28759v1 Announce Type: new Abstract: In X-ray CT, metallic objects cause beam hardening, photon starvation, and scattering, leading to projection inconsistency, streaks, dark bands, and structural distortions that compromise clinical diagnosis and quantitative analysis. Existing metal artifact reduction (MAR) methods remain limited: optimization-based methods may leave residual artifacts or blur structures, regression networks may generalize poorly across scenarios, and generative mod...

03.08.2026
Blog LLMs & Texto

NVIDIA AI Releases Molt: A PyTorch-Native Agentic Reinforcement Learning Framework

Agentic RL research is constant algorithm modification, and in mainstream frameworks every change threads through trainer, distributed backend, and rollout glue. NVIDIA's Molt targets that cost with about 8.6K lines of RL code, composing Ray, vLLM, and NeMo AutoModel around one asynchronous loop. The agent stays ordinary Python, trajectories stay token-exact, and throughput comes out statistically comparable to a Megatron-based stack. The post NVIDIA AI Releases Molt: A PyTorch-Native Agentic Re...

02.08.2026
AMD Releases Instella-MoE-16B-A3B: A Fully Open Mixture-of-Experts LLM With 2.8B Active Parameters Trained On Instinct GPUs
Blog LLMs & Texto

AMD Releases Instella-MoE-16B-A3B: A Fully Open Mixture-of-Experts LLM With 2.8B Active Parameters Trained On Instinct GPUs

AMD released Instella-MoE-16B-A3B, a fully open Mixture-of-Experts language model trained from scratch on Instinct MI300X and MI325X GPUs. It holds 16B total parameters but activates only 2.8B per token, using Gated MLA and FarSkip-Collective. AMD published weights from every training stage, plus data mixtures, configs, and inference code. The post AMD Releases Instella-MoE-16B-A3B: A Fully Open Mixture-of-Experts LLM With 2.8B Active Parameters Trained On Instinct GPUs appeared first on MarkTec...

01.08.2026
Blog Dados & Embeddings

LingBot-Map Tutorial: GPU-Aware Inference and Point Cloud Export

Discover how to implement a streaming 3D reconstruction pipeline using LingBot-Map. From GPU-aware configuration and preprocessing to GCTStream model inference and point cloud generation, this guide walks you through the steps to convert image or video sequences into consistent 3D scenes with exportable PLY and NPZ artifacts. The post LingBot-Map Tutorial: GPU-Aware Inference and Point Cloud Export appeared first on MarkTechPost .

31.07.2026
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