Search: “deployment”

DecompressionLM: Deterministic, Diagnostic, and Zero-Shot Concept Graph Extraction from Language Models

arXiv:2602.00377v3 Announce Type: replace Abstract: Existing knowledge probing methods rely on pre-defined queries, limiting extraction to known concepts. We introduce DecompressionLM, a stateless fra

researcharxiv-cs-cl

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Model Releases

Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each

DGX agent

Dense models activate all of their parameters for each token, whereas a Mixture‑of‑Experts (MoE) model loads all experts into memory but activates only a subset—e.g., Nemotron 3.5 Lightning has 30 B t

model-releasesnvidia-developer

15 Sept 2026

Design and Embedded Validation of Compact ML Models for Affective Touch Classification in a Soft Interactive Companion

arXiv:2607.16196v2 Announce Type: replace Abstract: Soft plush companions provide a safe and intuitive platform for affective human-robot interaction, but their deformable structure and distributed ta

researcharxiv-cs-ai

Does Reasoning Improve Psychological Depth in Large Language Models? It Depends on Who's Judging

model-releasesarxiv-cs-cl

arXiv:2609.13773v1 Announce Type: cross Abstract: LLM-as-a-Judge evaluators are increasingly used to score open-ended generation, yet a judge's correlation with human ratings on its development set ma

DreamSat-Bench: Development and Initial Testing of a Testbed for AI-Based Pose Estimation from 3D Reconstruction

model-releasesarxiv-cs-ro

arXiv:2609.14183v1 Announce Type: new Abstract: This paper presents the development and initial testing of DreamSat-Bench, a modular rendezvous and proximity operation testbed designed to benchmark AI

Tutorials

DTI-Guided Volumetric Spherical Harmonics Regression for Single-to-Multi-Shell dMRI Synthesis

arXiv:2609.14312v1 Announce Type: new Abstract: Multi-shell diffusion MRI (dMRI) unlocks more expressive microstructural modeling than single-shell scans, yet its longer acquisition time hinders deplo

tutorialsarxiv-cs-cv

Echo-E^3Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation

arXiv:2503.17543v4 Announce Type: replace-cross Abstract: Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements r

researcharxiv-cs-cv

Efficiency Hallucination: Formalizing and Measuring Behavioral Calibration in LLM-Based Code Optimization

arXiv:2609.14839v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Halluci

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

Applications

Ergodic Trajectory Planning with Dynamic Sensor Footprints

arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl

applicationsarxiv-cs-ro

Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return

model-releasesarxiv-cs-cl

arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o

FedLTLib: A Comprehensive Benchmark for Federated Long-Tail Learning

arXiv:2609.15625v1 Announce Type: cross Abstract: Driven by the escalating demand for privacy-preserving computing, Federated Learning (FL) has witnessed remarkable progress, becoming a cornerstone te

Follow the Geometry, Not the Model: Cold Start Semi-Supervised Learning

arXiv:2609.14451v1 Announce Type: cross Abstract: Modern semi-supervised learning (SSL) couples pseudo-label generation and classifier training, using the classifier's own confidence to select the pse

researcharxiv-cs-ai

From Prediction to Decision: World-Model-Guided Action Selection for Continuous Pile Excavation

arXiv:2609.15382v1 Announce Type: new Abstract: Wheel-loader excavation is a sequential decision problem in which every scoop changes the terrain available to subsequent actions. A practical world mod

safetyarxiv-cs-ro

From Visual Feedback to Textual Reviews: A Multi-Agent Vision-Language Framework for Image-Grounded Review Assistance

arXiv:2609.14761v1 Announce Type: cross Abstract: Visual feedback in the form of user-uploaded images and videos is becoming increasingly common in e-commerce platforms because it provides authentic e

Generate to Explore, Select to Exploit: Aligning LLM-based Headline Generation with Personalized Recommendation

arXiv:2609.15094v1 Announce Type: cross Abstract: In industrial recommendation feeds, presenting a static headline for an item often fails to satisfy the diverse, multimodal interests of the user popu

safetyarxiv-cs-ai

Tutorials

Generative AI and Extended Reality in Collaborative Architectural Design Education: An Exploratory Studio Study

arXiv:2609.13494v1 Announce Type: cross Abstract: Architectural design education relies heavily on visual ideation and representation to support collaborative learning in studio environments. Recent a

tutorialsarxiv-cs-ai

Generative Interpretability via Scalable Neuro-Symbolic Models

arXiv:2609.13529v1 Announce Type: cross Abstract: As the use of Large Language Models moves from chatbots into agentic systems, where outputs become actions with irreversible consequences on reality,

GeoSkill:Experience-Driven Hierarchical Skill Learning with Collaborative Revision forGeospatialAgents

arXiv:2609.13667v1 Announce Type: new Abstract: Geospatial agents are increasingly expected to support recurring and evolving analytical tasks rather than execute isolated workflows. In such settings,

Goal-Oriented Communications for Physical AI: Design and Testbed

arXiv:2609.15895v1 Announce Type: new Abstract: Physical AI relies on frequently-updated, latency-sensitive video stream to perceive, reason, and interact with the physical world, resulting in strict

hardwarearxiv-cs-ro

Governing at Machine Speed: An Adaptive Intelligence Architecture for Real-Time AI Policy Enforcement

arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifie

safetyarxiv-cs-ai

Graph-Transformer Fraud Detection with Self-Supervised Pretraining and Conformal Risk Control

arXiv:2609.14234v1 Announce Type: cross Abstract: Financial fraud in corporate transaction networks has grown more coordinated and harder to detect with rule-based engines and with classical learning

GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data

arXiv:2609.15571v1 Announce Type: new Abstract: As deep learning models become fundamental to modern healthcare, the 'Right to be Forgotten' mandated by privacy regulations like GDPR and HIPAA necessi

GzDRL: Reproducible and Scalable Deep Reinforcement Learning with Gazebo

arXiv:2609.13243v1 Announce Type: cross Abstract: We present GzDRL, a novel single-process reinforcement learning (RL) framework for Gazebo that overcomes longstanding bottlenecks in scalable, reprodu

hardwarearxiv-cs-lg

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate

agentsarxiv-cs-ro

I trained a 44M parameter quantized LLM from scratch on 45B tokens. It ships in 19.8 MB and runs at ~1,900 tok/s on CPU. [P]

model-releasesr-machinelearning

Three weeks back , i posted SHADOW-250M here. It got 360 upvotes, 293 on r/LocalLLaMA and 94 GitHub stars. Thank you. That model was 60 MB, ran around 400 tok/s on CPU and could retrieve records from

Introducing Filestore agent volumes: fully managed storage for agent workspaces

model-releasesgoogle-cloud-ai

From running build tools, to data analysis pipelines, to collaborative research, executing data-driven tasks is essential for any enterprise agent. Today, platform teams often stitch together custom w

Legislating World-Model-Based Planning with Legal Reasoning

arXiv:2609.15113v1 Announce Type: cross Abstract: As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning le

safetyarxiv-cs-ai

Applications

LIMODENet: Attention-Free Compact Encoders for Information-Preserving Onboard Satellite Image Restoration

arXiv:2609.14690v1 Announce Type: new Abstract: Onboard satellites must restore a channel-degraded image on a few watts, using neuromorphic accelerators (e.g., BrainChip Akida, Intel Loihi-2) that sup

applicationsarxiv-cs-cv

Machine Learning under Imperfect Data: Challenges and Methods

model-releasesarxiv-cs-lg

arXiv:2609.13914v1 Announce Type: new Abstract: Machine-learning models are commonly developed under an assumption that training and test data are sufficiently complete, balanced, labelled, and drawn

Local Ai

MANE: A Multi-Path Adaptive Network for Edge Onloading of Deep Neural Networks

arXiv:2609.14660v1 Announce Type: cross Abstract: Split computing constitutes a widely used distributed inference approach, where a lightweight head model is onloaded onto the device and a heavier tai

local-aiarxiv-cs-ai

MemRiskBench: Trace-Aware Risk-Preserving Evaluation for Long-Horizon LLM Agents

arXiv:2609.14976v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate memory across sessions, creating sparse but high-impact risks: stale facts, conflicting updates, cross-user leakage,

Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States

model-releasesarxiv-cs-cl

arXiv:2609.15972v1 Announce Type: new Abstract: As language models become more capable, long-term collaboration in learning, reasoning, and decision-making calls for a deeper understanding of the peop

One Feedback System Does Not Fit All: Localising Data-to-Text Driver Coaching for the United Kingdom and Nigeria

arXiv:2609.14687v1 Announce Type: new Abstract: Data-to-text driver coaching is often presented as a generic pipeline from telematics events to advice. This paper argues that its content requires loca

safetyarxiv-cs-cl

Oops, Not Now: PEARL, a RAG-Based Support Agent for Gameplay and What Players Want from AI Help

arXiv:2609.13718v1 Announce Type: cross Abstract: AI-powered gameplay support agents hold promise for game-based learning, yet grounding generative models in structured game data remains an open chall

Operational Range Bounding in Spectroscopy: A Safety Cage Framework for Machine Learning Models

arXiv:2609.13514v1 Announce Type: new Abstract: Ensuring the reliability of black-box machine learning models in safety-critical space missions remains a significant challenge, particularly when groun

safetyarxiv-cs-lg

Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data

model-releasesarxiv-cs-lg

arXiv:2609.13940v1 Announce Type: new Abstract: Effective anomaly detection frameworks are a central pillar of the Industry 4.0 paradigm. In this paper, we introduce an Optimal Transport (OT)-based fr

Optimizing Sparse Outcomes Through Dense Behavioral Signals via Value-Guided Preference Distillation

arXiv:2609.14648v1 Announce Type: new Abstract: Aligning multi-turn dialogue agents is usually framed as matching turn-level human preferences, yet direct optimization of long-term outcomes is often i

safetyarxiv-cs-cl

OpWeave: Flexible Operator Disaggregation for Heterogeneous LLM Serving

arXiv:2609.14237v1 Announce Type: cross Abstract: LLM serving systems increasingly disaggregate inference into finer-grained stages, with recent approaches separating attention from FFN or MoE executi

hardwarearxiv-cs-ai

Partition-Aware Scheduling for Mobile Heterogeneous Inference Co-Execution

arXiv:2609.14213v1 Announce Type: cross Abstract: Modern mobile inference runs on heterogeneous platforms combining mobile GPUs with multiple CPU core clusters. Existing optimizations typically exploi

hardwarearxiv-cs-lg

Pedestrian Crossing Intent Classification From Event-Based Vision Using Convolutional Spiking Neural Networks With Temporal Augmentation

arXiv:2609.13328v1 Announce Type: cross Abstract: Anticipating whether a pedestrian will cross the road is safety-critical for autonomous vehicles, requiring real-time inference under challenging cond

Planning or Learning: Reliability and Cost in Multi-Asset Maintenance

arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational co

PredTac: Learning Contact-Rich Manipulation with Predicted Touch

arXiv:2609.15198v1 Announce Type: new Abstract: Contact-rich manipulation benefits from tactile feedback, yet physical tactile sensors introduce hardware, calibration, synchronization, and maintenance

safetyarxiv-cs-ro

Applications

Prefix Sharing Is a Sorting Problem

arXiv:2609.13692v1 Announce Type: cross Abstract: LLM serving reuses KV cache by exact prefix match, so when a prompt is assembled from a set of reusable pieces -- retrieved passages, tool definitions

applicationsarxiv-cs-cl

PuzzleMate: Benchmarking MLLMs for Egocentric Puzzle Assistance

model-releasesarxiv-cs-cv

arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a

Rethinking Correctness for Uncertainty Estimation in Clinical Prediction with Vision-Language Models

arXiv:2609.15180v1 Announce Type: new Abstract: Vision-language models are increasingly explored for clinical prediction from electronic health records and medical images, where identifying unreliable

researcharxiv-cs-lg

Robust and Efficient Communication for Multi-Agent Learning

arXiv:2609.15361v1 Announce Type: cross Abstract: Effective communication is a cornerstone of distributed intelligence in Multi-Agent Reinforcement Learning (MARL), yet ensuring that generated message

RSIAgent: Autonomous Exploration for Recursive Self-improvement in New Environments

arXiv:2609.15364v1 Announce Type: new Abstract: Digital agents must often adapt to new environments whose interfaces, tools, and failure modes are not fully captured by pretrained models. We introduce