Search: “inference”

Vision-Language Procedural Reasoning for Context-Aware Reward Modeling of Robotic Endovascular Guidewire Navigation

arXiv:2606.30698v1 Announce Type: new Abstract: Robotic-assisted endovascular interventions demand accurate, stable, and context-aware guidewire navigation in complex and patient-specific vascular ana

safetyarxiv-cs-ro

1 Jul 2026

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Research

AsyncMDE: Real-Time Monocular Depth Estimation via Asynchronous Spatial Memory

DGX agent

arXiv:2603.10438v2 Announce Type: replace-cross Abstract: Foundation-model-based monocular depth estimation offers a viable alternative to active sensors for robot perception, yet its computational co

researcharxiv-cs-cv

30 Jun 2026

Beyond Triplet Plausibility: Relation Set Completion in Knowledge Graphs

arXiv:2606.29860v1 Announce Type: new Abstract: Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications. Due to their inherent incompleteness, knowle

Code Reasoning for Software Engineering Tasks: A Survey and A Call to Action

arXiv:2506.13932v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. Their performance on

agentsarxiv-cs-ai

CoLR-Det: Collaborative Latent Restoration for Small Object Detection in Low-Resolution Remote Sensing Images

arXiv:2601.12507v2 Announce Type: replace Abstract: Low-resolution remote sensing small object detection is limited by both missing visual details and the ambiguity of how details serve detection. Exi

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures

model-releasesarxiv-cs-lg

arXiv:2606.30064v1 Announce Type: new Abstract: We introduce a data-driven probabilistic framework for learning systems based on Gibbs measures on hierarchical structures. Unlike standard empirical ri

Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphs

arXiv:2606.30093v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucinations in Large Language Models (LLMs) by grounding the generation process on external knowledge.

researcharxiv-cs-cl

Factorizable Normalizing Flows for parameter-dependent density morphing

model-releasesarxiv-cs-lg

arXiv:2606.30489v1 Announce Type: cross Abstract: Normalizing Flows excel at modeling a single fixed density, yet many problems across the sciences, such as high energy physics, instead require modeli

Fast Enough to Act: Spatio-Temporal Visual Token Merging for Low-Latency Robotic VLMs and VLAs

arXiv:2606.29350v1 Announce Type: cross Abstract: Vision-language models and vision-language action models endow the robot with unprecedented capabilities. However, the input of video and high-resolut

safetyarxiv-cs-ai

Fast Wireless Foundation Models with Early-Exits

arXiv:2606.29640v1 Announce Type: cross Abstract: While wireless foundation models (FMs) are demonstrating strong potential to enable AI-Native 6G networks, their high computational cost remains a cri

researcharxiv-cs-ai

Tutorials

For even higher speeds, reach out for a custom deployment! We’ve hit 446 tok/s on Artificial Analysis. Learn more → https://fireworks.ai/blo…

Fireworks AI announced achieving 446 tokens per second throughput speeds as measured by Artificial Analysis benchmarks, positioning this as their standard performance metric. The company offers custom

tutorialsfireworks-ai--x

General and Efficient Steering of Diffusion Models

arXiv:2602.11395v2 Announce Type: replace-cross Abstract: Steering diffusion models toward conditions unseen during training typically requires either retraining with conditional inputs or per-step gr

safetyarxiv-cs-ai

GLACIER: Rethinking Mass Spectrum Prediction as an Object Detection Problem

arXiv:2606.29161v1 Announce Type: new Abstract: Predicting tandem mass spectra (MS/MS) from molecular structures represents a central task in analytical chemistry with direct relevance to clinical met

researcharxiv-cs-lg

How Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation

arXiv:2606.29809v1 Announce Type: cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-in

Hardware

It's wild how quickly Etched designed and got the chips out, all within 2 years. They went deep, hardcoding attention into silicon and getti…

It's wild how quickly Etched designed and got the chips out, all within 2 years. They went deep, hardcoding attention into silicon and getting very high MFU. This kind of hardware tailored made for LL

hardwareswyx--x

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators

arXiv:2606.28421v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models typically require substantial computational resources and cloud infrastructure, posing significant challenges for

Labeling Training Data for Entity Matching Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.28823v1 Announce Type: new Abstract: Recent large language models (LLMs) achieve strong performance on entity matching without requiring task-specific training data. However, applying these

LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation

arXiv:2606.30108v1 Announce Type: new Abstract: RECIST diameter measurements are widely used for tumor response assessment, but they provide only a limited 2D description of lesion extent. We present

LLM-Guided Planning for Multi-hop Reasoning over Multimodal Nuclear Regulatory Documents

arXiv:2606.29399v1 Announce Type: new Abstract: Reviewing nuclear regulatory documents requires multi-hop reasoning across tens of thousands of pages, where judgments depend on evidence assembled acro

Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization

arXiv:2602.06989v2 Announce Type: replace-cross Abstract: Carbonate reservoirs offer significant capacity for subsurface carbon storage, oil production, and underground hydrogen storage. X-ray compute

applicationsarxiv-cs-lg

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

arXiv:2606.28911v1 Announce Type: new Abstract: Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced com

researcharxiv-cs-lg

Local Ai

MatchAttention: Embedding Explicit Matching Constraints into Attention for Efficient Stereo Matching

arXiv:2510.14260v3 Announce Type: replace Abstract: Standard attention mechanisms are not well suited to stereo matching. Global attention scales quadratically and provides no explicit matching constr

local-aiarxiv-cs-cv

Multi-Block Diffusion Language Models

arXiv:2606.29215v1 Announce Type: cross Abstract: Block Diffusion Language Models (BD-LMs) improve diffusion-based text generation with KV caching and flexible-length generation. A natural next step i

researcharxiv-cs-cl

OpenSPM: An Environment-Transferable Robotic Key Spatial Pose Memory and Closed-Loop High-Frequency Flow-Matching Action Generation Model

arXiv:2606.29936v1 Announce Type: new Abstract: Open-environment tabletop robotic manipulation requires systems to possess semantic understanding, precise geometric pose estimation, and high-frequency

researcharxiv-cs-ro

ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified Recommendation

arXiv:2606.28357v1 Announce Type: cross Abstract: Recent advances in multimodal recommenders excel at feature fusion but remain opaque and inefficient decision-makers, lacking explicit reasoning and s

agentsarxiv-cs-ai

RiverONE: Generating Knowledge-Intensive VLM by Simulated Quantum Machines

arXiv:2606.29966v1 Announce Type: cross Abstract: Quantum computing provides a powerful paradigm for representing and transforming high-dimensional information through superposition, entanglement, and

RoamFlow: Reinforcement-Aligned One-Step Action MeanFlow Policy for Image-Goal Navigation

arXiv:2606.29934v1 Announce Type: new Abstract: Image-goal navigation is a key challenge in embodied robotics, where an agent must reach a target specified solely by a goal image. While existing reinf

safetyarxiv-cs-ro

S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence

model-releasesarxiv-cs-cv

arXiv:2606.20515v2 Announce Type: replace Abstract: Real-world spatial intelligence requires reasoning over a continuous and evolving 3D world, yet existing VLMs and tool-augmented agents largely rema

SATB-VR: Training Few-Step Video Restoration Diffusion Model using SNR-Aware Trajectory Blending

arXiv:2606.28677v1 Announce Type: new Abstract: While diffusion models excel in video restoration, their reliance on extensive iterative steps limits efficiency. Conversely, aggressive single-step dis

applicationsarxiv-cs-cv

Self-Supervised Calibration of Scientific Instruments Using Physical Consistency Constraints

arXiv:2606.29466v1 Announce Type: new Abstract: Calibration remains one of the principal obstacles to the deployment of machine learning in scientific instrumentation because it typically relies on ex

agentsarxiv-cs-lg

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping

arXiv:2606.29983v1 Announce Type: cross Abstract: Looped Transformers, which repeatedly apply a shared transformer block, are an architecturally natural fit for variable-length algorithmic tasks. Alth

researcharxiv-cs-ai

TF-MoE: Time-Frequency Mixture-of-Experts for Efficient Speech Separation

arXiv:2606.29575v1 Announce Type: cross Abstract: Recent advances in speech separation (SS) have led to compact front-end models with small parameter sizes, yet their high computational cost remains a

UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image

arXiv:2606.30608v1 Announce Type: new Abstract: Articulated 3D objects are essential for interactive environments in embodied AI, robotics, and virtual reality, but reconstructing their structure and

agentsarxiv-cs-cv

ViewSplat: View-Adaptive 3D Gaussian Splatting for Feed-Forward Synthesis

arXiv:2603.25265v2 Announce Type: replace Abstract: We present ViewSplat, a view-adaptive 3D Gaussian splatting network for novel view synthesis from unposed images. While recent feed-forward 3D Gauss

Bifocal Diffusion Language Models: Asymmetric Bidirectional Context for Parallel Generation

arXiv:2606.27732v1 Announce Type: cross Abstract: Discrete diffusion language models (dLLMs) recover masked tokens in parallel, offering significant speedups over autoregressive (AR) generation. Howev

researcharxiv-cs-ai

HunyuanImage 3.0 Technical Report

arXiv:2509.23951v3 Announce Type: replace Abstract: We present HunyuanImage 3.0, a native multimodal model that unifies multimodal understanding and generation within an autoregressive framework, with

safetyarxiv-cs-cv

LocalNav: Distilling Frontier VLMs and Embodied RL for On-Device Object Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2606.27871v1 Announce Type: new Abstract: Vision Language Models (VLMs) have emerged in the robotic domain as a powerful tool that enables environmental perception with language context, serving

NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning

arXiv:2606.27826v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only

RPM-Distill: Physiology-guided Adaptive Cross-modal Distillation for Robust Remote Physiological Measurement

arXiv:2606.28089v1 Announce Type: new Abstract: Video-based remote physiological measurement (RPM) is highly accessible but remains fragile under varying illumination, skin tones, and motion. Radio fr

safetyarxiv-cs-cv

StableMotion: One-Step Motion Estimation with Diffusion Prior

arXiv:2505.06668v2 Announce Type: replace Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion

Hardware

America is about to lose the AI race, and it will not happen at the frontier. It will happen at the floor. Everyone is watching who ships th…

America is about to lose the AI race, and it will not happen at the frontier. It will happen at the floor. Everyone is watching who ships the smartest model. The actual war is over the 80% of tokens n

hardwareclem-delangue--x

27 Jun 2026

Continual Robot Policy Learning via Variational Neural Dynamics

arXiv:2606.27353v1 Announce Type: new Abstract: Robots deployed in the real world rarely operate under a single fixed dynamics model: wind changes, payloads vary, batteries drain, contacts shift, and

safetyarxiv-cs-ro

Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance

arXiv:2606.27371v1 Announce Type: new Abstract: State-of-the-art flow models generate stunning images from text or image prompts. However, they suffer from diversity collapse when generating multiple

safetyarxiv-cs-cv

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

arXiv:2606.26120v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirect

researcharxiv-cs-cl

Epiphany-Aware KV Cache Eviction Without the Attention Matrix

arXiv:2606.26472v1 Announce Type: cross Abstract: As reasoning models emit chains of thought tens of thousands of tokens long, KV cache increasingly becomes a deployment bottleneck. Existing cache evi

applicationsarxiv-cs-cl

History-Conditioned Spatio-Temporal Visual Token Pruning for Efficient Vision-Language Navigation

arXiv:2603.06480v2 Announce Type: replace Abstract: Vision-Language Navigation (VLN) enables robots to follow natural-language instructions in visually grounded environments, serving as a key capabili

applicationsarxiv-cs-ro

Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems

model-releasesarxiv-cs-lg

arXiv:2606.26592v1 Announce Type: cross Abstract: We propose latent-space diffusion posterior sampling (L-DPS), an approximate Bayesian framework for high-dimensional inverse problems governed by part

Local Ai

Learning Adversarial Augmentation Policies for Robust Garlic Seedling Detection

arXiv:2606.26828v1 Announce Type: new Abstract: Accurate seedling detection during early growth stages is essential for timely replanting and effective crop management in precision agriculture. Howeve

local-aiarxiv-cs-cv