Search: “deployment”

Ask the Tool, Don't Guess: Agent Tool Calls Hold Their Progress, and the Serving System Should Read It

arXiv:2609.18849v1 Announce Type: cross Abstract: An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time. Serving systems decide whet

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

DGX agent

arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety

safetyarxiv-cs-ai

17 Sept 2026

Characterizing Replay Retention Under Dynamics Shift in Model-Based Reinforcement Learning

arXiv:2609.18167v1 Announce Type: cross Abstract: Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful. In continual model-based

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n

safetyarxiv-cs-ai

Decoder-Agnostic Token Merging for Vision Transformers: A Systematic Study of G2TM

arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha

researcharxiv-cs-cv

Designing Agentic AI Workflow Portfolios under Imperfect Selection and Compute Cost

arXiv:2609.18126v1 Announce Type: new Abstract: Agentic AI systems often approach the same task through multiple workflows that differ in reasoning strategy, verification structure, and compute cost.

safetyarxiv-cs-ai

DistAL: Distance-based Advantage Learning for VLA Fine-Tuning

arXiv:2609.18392v1 Announce Type: new Abstract: Vision-language-action models (VLAs) have trans- formed the field of robotic manipulation in recent years by combining the semantic understanding of LLM

DRT&R: Direct Radar Teach & Repeat

arXiv:2609.17766v1 Announce Type: new Abstract: Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke,

researcharxiv-cs-ro

EdgeReMIND: A Scalable, Top-Ranked Memorization Baseline for Temporal Multi-Relational Link Prediction

arXiv:2609.17916v1 Announce Type: new Abstract: Temporal link prediction on the Temporal Graph Benchmark 2.0 (TGB 2.0) faces a scalability ceiling: on the benchmark's three largest datasets, every exi

Evidence-Grounded Agentic Formulation Development in an Autonomous Laboratory

arXiv:2609.19099v1 Announce Type: new Abstract: Self-emulsifying drug delivery systems (SEDDS) can improve the oral bioavailability of poorly soluble drugs, but identifying high-performing formulation

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-

safetyarxiv-cs-ai

Agents

EvoUndo: Recoverability-Constrained Self-Evolution for LLM Agent Harnesses

arXiv:2608.28363v2 Announce Type: replace Abstract: LLM agents increasingly modify their own prompts, tools, middleware, resources, and execution harnesses at runtime. Such self-evolution can improve

agentsarxiv-cs-ai

FedASAP: Activation Statistics-driven Structured Adaptive Pruning for Efficient Personalized Federated Learning for Lesion Segmentation on brain MRI

model-releasesarxiv-cs-cv

arXiv:2609.19042v1 Announce Type: cross Abstract: In medical imaging, developing robust deep learning models requires data from various domains. However, regulatory policies protecting patient privacy

FRAUDSkill: Structured Frozen-Weight Skill Optimization for Audio Anti-Fraud Detection

model-releasesarxiv-cs-cl

arXiv:2609.18766v1 Announce Type: cross Abstract: Large audio-language models have shown promise for anti-fraud detection by directly processing speech and reasoning over fraud-related evidence. Their

From Gameplay to Policy: Towards Scalable Robot Data Collection via Gamified Robot-Free Interaction

model-releasesarxiv-cs-ro

arXiv:2609.18650v1 Announce Type: new Abstract: Learning generalizable robot manipulation policies requires large-scale and diverse interaction data, yet collecting real-world demonstrations remains c

From Pixels to Pairs: A Comprehensive Benchmark of LLM-Based Key-Value Extraction in Noisy Document Settings

model-releasesarxiv-cs-cl

arXiv:2609.17538v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for structured information extraction from documents, yet their behavior under realistic OCR noise re

Function-Preserving Data Generation for Zero-Shot Real-to-Sim-to-Real Manipulation

arXiv:2609.18293v1 Announce Type: new Abstract: Robotic data generation is a promising paradigm for scaling robot learning without collecting large-scale real-world data. However, generating geometric

FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing

arXiv:2512.22143v2 Announce Type: replace-cross Abstract: Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communicatio

Agents

HINT-Plan: Human Intention-Aware Robot Task Planning in Context-Rich Environments using Vision Language Models

arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often

agentsarxiv-cs-ai

Hybrid coupling with numerics-informed neural networks and the overlapping Schwarz alternating method

arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using

researcharxiv-cs-lg

Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

arXiv:2609.18842v1 Announce Type: new Abstract: The scaling laws hold that a language model grows more capable with more parameters and more training data, and Mixture-of-Experts (MoE) architectures h

Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine

safetyarxiv-cs-cl

LaSeD: Label-Semantic Self-Distillation for Visual-Only Surgical Phase Recognition

arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post

researcharxiv-cs-cv

LightSleepX: A Lightweight, Inception-Based Dual-Modal Network for Sleep Staging

arXiv:2609.19062v1 Announce Type: new Abstract: Automatic sleep staging is fundamental to personal health monitoring, yet many existing approaches are ill-suited for real-world applications. Tradition

Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment

arXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these c

Locating Hidden Failures Makes Long-Horizon Agents More Reliable

arXiv:2609.17930v1 Announce Type: new Abstract: As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether th

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia. Structural MRI pro

NeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation

arXiv:2609.17699v1 Announce Type: new Abstract: We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive

On-the-Fly Homographies Calibration for Multi-Camera Tracking

arXiv:2609.18582v1 Announce Type: cross Abstract: Precise multi-camera tracking traditionally relies on rigorous 3D site calibration, yet this requirement is often operationally impossible in large-sc

Agents

One Axis, No Brake: Self-Knowledge Limits the Filtering of Harmful Peer Conformity in LLMs

arXiv:2609.18998v1 Announce Type: cross Abstract: Multi-agent LLM systems are expected to be more reliable because agents can catch each other's mistakes. But peer pressure cuts both ways: the same co

agentsarxiv-cs-cl

Applications

Online Robust Reinforcement Learning Through Monte-Carlo Planning

arXiv:2609.18599v1 Announce Type: cross Abstract: Monte Carlo Tree Search (MCTS) is a powerful framework for solving complex decision-making problems, yet it often relies on the assumption that the si

applicationsarxiv-cs-ai

Peak-Aware Short-Term Load Forecasting Across Distribution Grid Aggregation Levels

arXiv:2609.18588v1 Announce Type: new Abstract: For distribution system operators, short-term load forecasting (STLF) supports congestion management, voltage control, and asset protection. Most existi

researcharxiv-cs-lg

PESTO: Formally Correct Registration of LiDAR Point Clouds with Limited Overlap

arXiv:2609.18082v1 Announce Type: cross Abstract: In this paper we tackle the problem of aligning LiDAR point clouds also known as the point cloud registration problem. We propose a new algorithm, PES

Prior Evolution and Task Alignment for Aerial Grasping

arXiv:2609.18153v1 Announce Type: new Abstract: Aerial grasping is a remarkable capability exhibited by predatory birds, allowing them to capture prey through highly coordinated maneuvers in flight. I

Quanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs

arXiv:2609.18248v1 Announce Type: cross Abstract: An advanced retrieval-augmented generation pipeline is typically assembled from three or four independently operated systems: an approximate nearest-n

ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks

arXiv:2609.18595v1 Announce Type: new Abstract: Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit

researcharxiv-cs-lg

Reliable Virtual Sensing: A Multi-Domain Benchmark for Robustness Under Sensor Failures

arXiv:2609.18396v1 Announce Type: cross Abstract: Virtual sensing, the estimation of hard-to-measure quantities from available sensor measurements, is a critical enabler for control and monitoring in

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

Applications

Scaling Articulated Rationales for MLLM-based Recommendation

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these sign

applicationsarxiv-cs-ai

Securing quantum error correction against misleading advice from AI agents

arXiv:2609.19090v1 Announce Type: cross Abstract: Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity i

Size Matters: Foundation Model for Czech HTML documents

model-releasesarxiv-cs-cl

arXiv:2609.18494v1 Announce Type: new Abstract: Creating universal, high-quality representations of web documents in high-traffic industrial environments requires models that are both performant and e

Structural Inference under Hidden Agents

arXiv:2609.18045v1 Announce Type: new Abstract: Recovering latent interaction structures from multi-agent dynamics is important for understanding and predicting interacting systems. Trajectory-based s

Local Ai

Teaching AI, Robotics, & Community: A Hubs-Based K-12 Education Framework for Reaching Rural Schools

arXiv:2609.18072v1 Announce Type: new Abstract: K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship. Programs like FIRST provi

local-aiarxiv-cs-ai

Applications

The future of orchestration: Pine59’s journey to Airflow 3 on Google Cloud

applicationsgoogle-cloud-ai

Operating large data pipelines requires an orchestration layer that scales smoothly as workloads expand. When your pipelines process millions of complex data points every day to feed predictive models

Hardware

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a

hardwarearxiv-cs-ai

The Missing 'I Don't Know': Why Three Reasoning-Reliability Findings Converge on Calibrated Abstention

arXiv:2609.17686v1 Announce Type: cross Abstract: Three recent results describe what look like unrelated LLM reliability problems. Yin et al. (2026) show reasoning RL collapses tool-reliability repres

The Unbearable Weight: Scaling Models and Methods for UAV Audio Classification

arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp