Search: “deployment”

Elastic Spiking Transformers for Efficient Gesture Understanding

arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applica

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

DGX agent

arXiv:2605.14950v1 Announce Type: new Abstract: Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action gener

safetyarxiv-cs-cv

15 May 2026

G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

model-releasesarxiv-cs-cv

arXiv:2512.02482v2 Announce Type: replace Abstract: We propose G-SHARP, a commercially compatible, real-time surgical scene reconstruction framework designed for minimally invasive procedures that req

Hardware

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU

arXiv:2605.14839v1 Announce Type: new Abstract: Traditional methods for classifying global navigation satellite system (GNSS) jamming signals typically involve post-processing raw or spectral data str

hardwarearxiv-cs-lg

Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations

arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m

agentsarxiv-cs-ai

In-Context Learning for Data-Driven Censored Inventory Control

model-releasesarxiv-cs-lg

arXiv:2605.14840v1 Announce Type: new Abstract: We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determin

Learning Cross-Coupled and Regime Dependent Dynamics for Aerial Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.14805v1 Announce Type: new Abstract: Accurate dynamics models are critical for aerial manipulators operating under complex tasks such as payload transport. However, modeling these systems r

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study

arXiv:2605.14087v1 Announce Type: new Abstract: Large Language Models (LLMs), when trained on web-scale corpora, inherently absorb toxic patterns from their training data. This leads to ``toxic degene

safetyarxiv-cs-cl

PEML: Parameter-efficient Multi-Task Learning with Optimized Continuous Prompts

arXiv:2605.14055v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for various tasks. Recently, there has been an increas

REALM: Retrospective Encoder Alignment for LFP Modeling

arXiv:2605.14867v1 Announce Type: cross Abstract: Spike activity has been the dominant neural signal for behavior decoding due to its high spatial and temporal resolution. However, as brain-computer i

SR-Platform: An Agentic Pipeline for Natural Language-Driven Robot Simulation Environment Synthesis

arXiv:2605.14700v1 Announce Type: new Abstract: Generating robot simulation environments remains a major bottleneck in simulation-based robot learning. Constructing a training-ready MuJoCo scene typic

agentsarxiv-cs-ro

SuperADD: Training-free Class-agnostic Anomaly Segmentation -- CVPR 2026 VAND 4.0 Workshop Challenge Industrial Track

arXiv:2605.14808v1 Announce Type: new Abstract: Visual anomaly detection (AD) for industrial inspection is a highly relevant task in modern production environments. The problem becomes particularly ch

applicationsarxiv-cs-cv

Welcome to BlackFile: Inside a Vishing Extortion Operation

model-releasesgoogle-cloud-ai

Written by: Austin Larsen, Tyler McLellan, Genevieve Stark, Dan Ebreo Introduction Google Threat Intelligence Group (GTIG) has continued to track an expansive extortion campaign by UNC6671, a threat a

Compact Latent Manifold Translation: A Parameter-Efficient Foundation Model for Cross-Modal and Cross-Frequency Physiological Signal Synthesis

arXiv:2605.13248v1 Announce Type: cross Abstract: The analysis of physiological time series, such as electrocardiograms (ECG) and photoplethysmograms (PPG), is persistently hindered by modality and fr

Context Matters: Auditing Gender Bias in T2I Generation through Risk-Tiered Use-Case Profiles

arXiv:2605.13113v1 Announce Type: cross Abstract: Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting

safetyarxiv-cs-ai

CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions

arXiv:2605.12980v1 Announce Type: cross Abstract: Molecular structure elucidation from tandem mass spectra (MS/MS) remains challenging, particularly for de novo generation beyond database coverage. A

CoT-Guard: Small Models for Strong Monitoring

arXiv:2605.12746v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of reasoning models is a promising approach for detecting covert misbehavior (i.e., hidden objectives) in code g

Decision Support for Marketplace Policies under Incomplete Evidence: From Replay to Launch Readiness

arXiv:2605.12840v1 Announce Type: cross Abstract: Marketplace platforms routinely evaluate pricing and allocation policies using logged observational data, yet strong offline performance does not impl

MinT: Managed Infrastructure for Training and Serving Millions of LLMs

arXiv:2605.13779v1 Announce Type: cross Abstract: We present MindLab Toolkit (MinT), a managed infrastructure system for Low-Rank Adaptation (LoRA) post-training and online serving. MinT targets a set

safetyarxiv-cs-ai

Research

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

arXiv:2605.12566v1 Announce Type: cross Abstract: The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicle (UAV) applications, including logistics, inspect

researcharxiv-cs-lg

Position: Assistive Agents Need Accessibility Alignment

arXiv:2605.13579v1 Announce Type: new Abstract: Assistive agents for Blind and Visually Impaired (BVI) users require accessibility alignment as a first-class design objective. Despite rapid progress i

safetyarxiv-cs-ai

What Limits Vision-and-Language Navigation ?

arXiv:2605.13328v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) is a cornerstone of embodied intelligence. However, current agents often suffer from significant performance degr

agentsarxiv-cs-ai

When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems

arXiv:2605.12947v1 Announce Type: cross Abstract: LLM-enabled AI workflows increasingly produce outputs through iterative generate-evaluate-revise loops. Each iteration can improve the candidate, but

agentsarxiv-cs-ai

Local Ai

Where Does Reasoning Break? Step-Level Hallucination Detection via Hidden-State Transport Geometry

arXiv:2605.13772v1 Announce Type: cross Abstract: Large language models hallucinate during multi-step reasoning, but most existing detectors operate at the trace level: they assign one confidence scor

local-aiarxiv-cs-ai

Ada-MK: Adaptive MegaKernel Optimization via Automated DAG-based Search for LLM Inference

model-releasesarxiv-cs-cl

arXiv:2605.11581v1 Announce Type: new Abstract: When large language models (LLMs) serve real-time inference in commercial online advertising systems, end-to-end latency must be strictly bounded to the

ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder

model-releasesarxiv-cs-lg

arXiv:2605.11091v1 Announce Type: new Abstract: Automated ASD screening tools remain limited by single-architecture evaluations, axis-restricted assessment, and near-exclusive focus on adult cohorts,

Attacks and Mitigations for Distributed Governance of Agentic AI under Byzantine Adversaries

arXiv:2605.12364v1 Announce Type: cross Abstract: Agentic AI governance is a critical component of agentic AI infrastructure ensuring that agents follow their owner's communication and interaction pol

agentsarxiv-cs-lg

Augmented Lagrangian Method for Last-Iterate Convergence for Constrained MDPs

arXiv:2605.11694v1 Announce Type: new Abstract: We study policy optimization for infinite-horizon, discounted constrained Markov decision processes (CMDPs). While existing theoretical guarantees typic

Efficient LLM-based Advertising via Model Compression and Parallel Verification

arXiv:2605.11582v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable potential in advertising scenarios such as ad creative generation and targeted advertising. However,

applicationsarxiv-cs-cl

Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance

arXiv:2605.12453v1 Announce Type: cross Abstract: To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cas

applicationsarxiv-cs-lg

Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.11354v1 Announce Type: new Abstract: Transformer-based 3D reconstruction has emerged as a powerful paradigm for recovering geometry and appearance from multi-view observations, offering str

Rethink the Role of Neural Decoders in Quantum Error Correction

arXiv:2605.12046v1 Announce Type: cross Abstract: Quantum error correction (QEC) is essential for enabling quantum advantages, with decoding as a central algorithmic primitive. Owing to its importance

RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning

arXiv:2605.11564v1 Announce Type: new Abstract: Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to sho

safetyarxiv-cs-ro

Robust Multi-Agent Path Finding under Observation Attacks: A Principled Adversarial-Plus-Smoothing Training Recipe

arXiv:2605.11469v1 Announce Type: new Abstract: Decentralized multi-agent path finding (MAPF) routes a team of agents on a shared grid, each acting from its own local view. The standard solution train

The Evaluation Differential: When Frontier AI Models Recognise They Are Being Tested

arXiv:2605.11496v1 Announce Type: cross Abstract: Recent published evidence from frontier laboratories shows that contemporary AI models can recognise evaluation contexts, latently represent them, and

Local Ai

A Reconfigurable Multiplier Architecture for Error-Resilient Applications in RISC-V Core

arXiv:2605.08785v1 Announce Type: cross Abstract: Neural Networks (NNs) have been widely adopted due to their outstanding efficacy and adaptability across computer vision and deep learning application

local-aiarxiv-cs-ai

AI- Enhanced Stethoscope in Remote Diagnostics for Cardiopulmonary Diseases

arXiv:2505.18184v2 Announce Type: replace-cross Abstract: The increase in cardiac and pulmonary diseases presents an alarming and pervasive health challenge on a global scale responsible for unexpecte

applicationsarxiv-cs-cv

Biosignal Fingerprinting: A Cross-Modal PPG-ECG Foundation Model

arXiv:2605.09579v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of global mortality, yet scalable cardiac monitoring is hindered by the gap between diagnostic-rich E

applicationsarxiv-cs-ai

Constraint-Aware Diffusion Priors for High-Fidelity and Versatile Quadruped Locomotion

arXiv:2605.08804v1 Announce Type: new Abstract: Reinforcement learning combined with imitation learning has significantly advanced biomimetic quadrupedal locomotion. However, scaling these frameworks

safetyarxiv-cs-ro

Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy

arXiv:2505.05707v2 Announce Type: replace Abstract: The integration of AI into daily life has generated considerable attention and excitement, while also raising concerns about automating algorithmic

Research

Deterministic Differentiable Structured Pruning for Large Language Models

arXiv:2603.08065v2 Announce Type: replace-cross Abstract: Structured pruning reduces LLM inference cost by removing low-importance architectural components. This can be viewed as learning a multiplica

researcharxiv-cs-cl

Echo-LoRA: Parameter-Efficient Fine-Tuning via Cross-Layer Representation Injection

arXiv:2605.08177v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has become a practical route for adapting large language models to downstream tasks, with LoRA-style methods be

Federated Language Models Under Bandwidth Budgets: Distillation Rates and Conformal Coverage

model-releasesarxiv-cs-cl

arXiv:2605.09986v1 Announce Type: cross Abstract: Training a language model on data scattered across bandwidth-limited nodes that cannot be centralized is a setting that arises in clinical networks, e

GRC: Unifying Reasoning-Driven Generation, Retrieval and Compression

arXiv:2605.09100v1 Announce Type: new Abstract: Text embedding and generative tasks are usually trained separately based on large language models (LLMs) nowadays. This causes a large amount of trainin

agentsarxiv-cs-cl

Local Ai

iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning

arXiv:2605.10732v1 Announce Type: cross Abstract: Automated transit payment analysis is vital for scalable fare auditing and passenger analytics, yet practice still relies on limited manual inspection

local-aiarxiv-cs-ai

LAQuant: A Simple Overhead-free Large Reasoning Model Quantization by Layer-wise Lookahead Loss

arXiv:2605.08755v1 Announce Type: new Abstract: Large reasoning models (LRMs) reach competition-level math and coding accuracy via long autoregressive decoding, making per-token decoding cost a primar

Log analysis is necessary for credible evaluation of AI agents

arXiv:2605.08545v1 Announce Type: new Abstract: Agent benchmarks typically report only final outcomes: pass or fail. This threatens evaluation credibility in three ways. First, scores may be inflated

Nano-U: Efficient Terrain Segmentation for Tiny Robot Navigation

arXiv:2605.10210v1 Announce Type: cross Abstract: Terrain segmentation is a fundamental capability for autonomous mobile robots operating in unstructured outdoor environments. However, state-of-the-ar

agentsarxiv-cs-cv