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techloy.com · Nov 5

Why Low-Latency AI Inference Matters for Real-Time Applications and AI Agents

Modern software architectures demand sub-millisecond execution to support complex user requests.

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arXiv

Nov 4

From Pixels to Actions - Towards Native Vision-Language-Action Policies

Vision-language-action models are typically built on a simple premise: perception is first compressed by visual encoders, and action reasoning begins only afterwards. Yet manipulation often hinges on precisely the visual signals most vulnerable to this abstraction, e.g., local geometry, boundaries, depth, and subtle state changes. This raises a fundamental question: should action policies inherit a fixed visual endpoint, or directly access evolving visual computation? We introduce NEO-VLA, a structurally encoder-free vision-language-action framework. Images are tokenized by lightweight patch convolutional layers and evolve jointly with language throughout the backbone, allowing a flow-matching action expert to draw from instruction-conditioned visual representations at different depths. This simple change reveals a consistent pattern. Native architectures outperform encoder-based counterparts under controlled comparisons; full fine-tuning reduces but does not erase the gap, and additional scale alone cannot recover it. More strikingly, layer-wise probing shows that the action-critical signals often peak well before the final visual representation. Across diverse manipulation…

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arXiv

Sep 18

What Should We Ask Next? Retrieval-Aware Question Learning for Interactive ReID

Interactive retrieval with partial evidence constitutes a sequential information-acquisition problem: an agent must choose questions that acquire useful evidence for the next retrieval update. Existing systems train this decision by imitating an offline ordering of candidate QA…

arXiv

Sep 18

Riemannian Simultaneous Inference for Tangent Vector Field Regression

We consider nonparametric tangent vector field regression on a Riemannian manifold without boundary. Because responses at different points lie in different tangent spaces, the proposed kernel estimator first parallel transports nearby responses to the target tangent space and…

arXiv

Sep 18

Beyond Kinematics: Benchmarking Simulation Fidelity for Muscle-Driven Imitation Learning

In this work, we conduct a systematic comparison of two state-of-the-art motion-imitation reinforcement learning (MIRL) pipelines, one built on SCONE/HyFyDy and one built on MuJoCo/MyoSim. HyFyDy emphasizes physiological realism through detailed musculotendon modeling, while…

arXiv

Sep 18

Intervention Granularity Matters: Coherent Treatment Bundles in Counterfactual Simulation with Clinical World Models

Counterfactual simulation with a clinical world model means fixing a patient's history, changing the treatment, and reading off the predicted response. Doing so requires deciding what counts as one intervention. In clinical settings, interventions are documented as bundles: a…

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