Search: “inference”

How Prompts Move Language Model Behavior: Frames, Salience, and Construal as Semantic Control

arXiv:2512.12688v3 Announce Type: replace-cross Abstract: Prompt engineering is widely used to shape large language model behavior, yet it is often treated as a practical heuristic rather than as a fo

researcharxiv-cs-cl

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Hardware

How to Build In-Vehicle AI Agents with NVIDIA: From Cloud to Car

DGX agent

The automotive cockpit is undergoing a fundamental shift from rule-based interfaces to agentic, multimodal AI systems capable of reasoning, planning, and acting. This is enabled by an agentic AI pipel

hardwarenvidia-developer

5 May 2026

Human Cognitive Benchmarks Reveal Foundational Visual Gaps in MLLMs

model-releasesarxiv-cs-cl

arXiv:2502.16435v4 Announce Type: replace-cross Abstract: Humans develop perception through a bottom-up hierarchy: from basic primitives and Gestalt principles to high-level semantics. In contrast, cu

Improving Model Safety by Targeted Error Correction

arXiv:2605.02544v1 Announce Type: cross Abstract: The widespread adoption of machine learning in critical applications demands techniques to mitigate high-consequence errors. Our method utilizes a dua

safetyarxiv-cs-cv

Introducing Agent Gateway ISV ecosystem for security and governance

model-releasesgoogle-cloud-ai

Managing agents and their actions can quickly grow in complexity and introduce security risks unique to AI. To address these challenges, at Google Cloud Next we announced Agent Gateway to provide simp

Language models recognize dropout and Gaussian noise applied to their activations

model-releasesarxiv-cs-ai

arXiv:2604.17465v2 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a certain degree, verbalize the difference between perturbations applied to th

Latent Space Probing for Adult Content Detection in Video Generative Models

arXiv:2605.00874v1 Announce Type: new Abstract: The rapid proliferation of AI-powered video generation systems has introduced significant challenges in content moderation, particularly with respect to

Local Ai

Linearizing Vision Transformer with Test-Time Training

arXiv:2605.02772v1 Announce Type: new Abstract: While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for overcoming the quadratic bottleneck, training such m

local-aiarxiv-cs-cv

LittleBit-2: Maximizing the Spectral Energy Gain in Sub-1-Bit LLMs via Latent Geometry Alignment

arXiv:2603.00042v2 Announce Type: replace Abstract: We identify the Spectral Energy Gain in extreme model compression, where low-rank binary approximations outperform tiny-rank floating-point baseline

LLM-Based Agentic Negotiation for 6G: Addressing Uncertainty Neglect and Tail-Event Risk

arXiv:2511.19175v2 Announce Type: replace-cross Abstract: A critical barrier to the trustworthiness of sixth-generation (6G) agentic autonomous networks is the uncertainty neglect bias; a cognitive te

safetyarxiv-cs-ai

Agents

llms are getting expensive why we need oss models

Large language models are becoming increasingly costly to develop and operate, creating a need for open-source alternatives that reduce dependency on expensive proprietary models and make AI more acce

agentsharrison-chase--x

Local Ai

Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers

arXiv:2509.15113v2 Announce Type: replace Abstract: The growing demand for energy-efficient, high-performance AI systems has led to increased attention on alternative computing platforms (e.g., photon

local-aiarxiv-cs-lg

Hardware

Maistros: A Greek Large Language Model Adapted Through Knowledge Distillation From Large Reasoning Models

arXiv:2605.01870v1 Announce Type: new Abstract: Large Language Models (LLMs) have substantially advanced the field of Natural Language Processing (NLP), achieving state-of-the-art performance across a

hardwarearxiv-cs-cl

Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score

arXiv:2605.02206v1 Announce Type: new Abstract: Machine unlearning in Vision-Language Models (VLMs) is required for compliance with the General Data Protection Regulation (GDPR), yet current evaluatio

MIRA: A Score for Conditional Distribution Accuracy and Model Comparison

arXiv:2605.02014v1 Announce Type: cross Abstract: We introduce Mira, a sample-based score for assessing the accuracy of a candidate conditional distribution using only joint samples from the true data

safetyarxiv-cs-lg

Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling

arXiv:2605.01676v1 Announce Type: cross Abstract: Missing data imputation remains a fundamental challenge in modern data science, especially when uncertainty quantification is essential. In this work,

Model Merging: Foundations and Algorithms

arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved

MOGO: Residual Quantized Hierarchical Causal Transformer for High-Quality and Real-Time 3D Human Motion Generation

arXiv:2506.05952v4 Announce Type: replace Abstract: Recent advances in transformer-based text-to-motion generation have led to impressive progress in synthesizing high-quality human motion. Neverthele

NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals

arXiv:2605.00871v1 Announce Type: cross Abstract: State space models (SSMs) achieve linear-time complexity but struggle with multi-channel physiological signals due to three limitations: fixed kernels

Tutorials

Natural Gradient Bayesian Filtering: Geometry-Aware Filter for Dynamical Systems

arXiv:2605.02306v1 Announce Type: new Abstract: Bayesian filtering is a cornerstone of state estimation in complex systems such as aerospace systems, yet exact solutions are available only for linear

tutorialsarxiv-cs-ro

Noise Steering for Controlled Text Generation: Improving Diversity and Reading-Level Fidelity in Arabic Educational Story Generation

arXiv:2604.03380v2 Announce Type: replace Abstract: Generating diverse, pedagogically valid stories for Arabic early-grade reading assessments requires balancing tight constraints on vocabulary, readi

researcharxiv-cs-cl

Object-Level Explanations for Image Geolocation Models: a GeoGuessr use-case

arXiv:2605.00912v1 Announce Type: new Abstract: When humans play geolocation games such as GeoGuessr, they rely on concrete visual cues, such as road markings, vegetation, or architectural details, to

On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length

arXiv:2605.02572v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise as interactive agents that solve tasks through extended sequences of environment interactions. While p

Agents

Optimizing Trajectory-Trees in Belief Space: An Application from Model Predictive Control to Task and Motion Planning

arXiv:2605.01860v1 Announce Type: new Abstract: This paper explores the benefits of computing arborescent trajectories (trajectory-trees) instead of commonly used sequential trajectories for partially

agentsarxiv-cs-ro

Physics-Informed Neural Learning for State Reconstruction and Parameter Identification in Coupled Greenhouse Climate Dynamics

arXiv:2605.02524v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for integrating data-driven learning with physical knowledge. In

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

arXiv:2605.00973v1 Announce Type: new Abstract: Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, m

Applications

Pixel-to-4D: Camera-Controlled Image-to-Video Generation with Dynamic 3D Gaussians

arXiv:2601.00678v2 Announce Type: replace Abstract: Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an ess

applicationsarxiv-cs-cv

Principles and Guidelines for Randomized Controlled Trials in AI Evaluation

arXiv:2605.02050v1 Announce Type: cross Abstract: This work establishes a foundational framework for standardizing AI evaluation RCTs (sometimes called human uplift studies). Drawing on established ex

Probabilistic Modeling of Multi-rater Medical Image Segmentation for Diversity and Personalization

arXiv:2512.00748v2 Announce Type: replace Abstract: Lesion segmentation is inherently influenced by imaging uncertainty, arising from ill-defined lesion boundaries and inter-observer variability in di

Psychologically Potent, Computationally Invisible: LLMs Generate Social-Comparison Triggers They Fail to Detect

model-releasesarxiv-cs-cl

arXiv:2605.01017v1 Announce Type: new Abstract: We introduce Xiaohongshu Social Comparison Reader Elicitation (XHS-SCoRE), a reader-grounded benchmark for detecting if a text-only Xiaohongshu (RedNote

Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training

arXiv:2511.07328v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) methods enhance LLM performance by efficiently filtering relevant context for LLMs, reducing hallucinations and

Referring Multiple Regions with Large Multimodal Models via Contextual Latent Steering

arXiv:2605.01827v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently demonstrated their proficiency in holistic visual comprehension. However, most of them struggle to tackle r

Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance

arXiv:2605.01325v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have enhanced traditional LLMs with visual capabilities through the integration of vision encoders. While recent works hav

safetyarxiv-cs-cv

Riemannian Generative Decoder

arXiv:2506.19133v3 Announce Type: replace Abstract: Euclidean representations distort data with intrinsic non-Euclidean structure. While Riemannian representation learning offers a solution by embeddi

Robo3R: Enhancing Robotic Manipulation with Accurate Feed-Forward 3D Reconstruction

arXiv:2602.10101v2 Announce Type: replace Abstract: 3D spatial perception is fundamental to generalizable robotic manipulation, yet obtaining reliable, high-quality 3D geometry remains challenging. De

safetyarxiv-cs-ro

Local Ai

Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

local-aiarxiv-cs-cv

SF20K Competition 2025: Summary and findings

arXiv:2605.01496v1 Announce Type: new Abstract: This report presents the results and findings of the first edition of the Short-Films 20K (SF20K) Competition, held in conjunction with the SLoMO Worksh

Applications

ShapeGrasp: Simultaneous Visuo-Haptic Shape Completion and Grasping for Improved Robot Manipulation

arXiv:2605.02347v1 Announce Type: new Abstract: Humans grasp unfamiliar objects by combining an initial visual estimate with tactile and proprioceptive feedback during interaction. We present ShapeGra

applicationsarxiv-cs-ro

SixthSense: Task-Agnostic Proprioception-Only Whole-Body Wrench Estimation for Humanoids

arXiv:2605.01427v1 Announce Type: new Abstract: Humanoid robots are entering our physical world at scale, yet as oversized toys--good at singing and dancing, but short on force-interaction capabilitie

researcharxiv-cs-ro

Skills as Verifiable Artifacts: A Trust Schema and a Biconditional Correctness Criterion for Human-in-the-Loop Agent Runtimes

arXiv:2605.00424v1 Announce Type: cross Abstract: Agent skills -- structured packages of instructions, scripts, and references that augment a large language model (LLM) without modifying the model its

safetyarxiv-cs-ai

Skipping the Zeros in Diffusion Models for Sparse Data Generation

arXiv:2605.01817v1 Announce Type: new Abstract: Diffusion models (DMs) excel on dense continuous data, but are not designed for sparse continuous data. They do not model exact zeros that represent the

Applications

SlimDiffSR: Toward Lightweight and Efficient Remote Sensing Image Super-Resolution via Diffusion Model Distillation

arXiv:2605.02198v1 Announce Type: new Abstract: Diffusion models have recently achieved remarkable performance in image super-resolution (SR), but their high computational cost limits practical deploy

applicationsarxiv-cs-cv

Space Network of Experts: Architecture and Expert Placement

arXiv:2605.00515v1 Announce Type: cross Abstract: Leveraging continuous solar energy harvesting at high efficiency, space data centers are envisioned as a promising platform for executing energy-inten

researcharxiv-cs-ai

SparseContrast: Dynamic Sparse Attention for Efficient and Accurate Contrastive Learning in Medical Imaging

arXiv:2605.00887v1 Announce Type: new Abstract: We propose SparseContrast, a new framework that merges dynamic sparse attention with contrastive learning for medical imaging, with a focus on chest X-r

Tutorials

SpecTM: Spectral Targeted Masking for Trustworthy Foundation Models

arXiv:2603.22097v2 Announce Type: replace-cross Abstract: Foundation models are now increasingly being developed for Earth observation (EO), yet they often rely on stochastic masking that do not expli

tutorialsarxiv-cs-lg

Split-on-Share: Mixture of Sparse Experts for Task-Agnostic Continual Learning

arXiv:2601.17616v2 Announce Type: replace Abstract: Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to

SteeringDiffusion: A Bottlenecked Activation Control Interface for Diffusion Models

arXiv:2605.01653v1 Announce Type: new Abstract: We introduce SteeringDiffusion, a bottlenecked activation-level control interface for diffusion models that exposes a smooth, monotonic, and runtime-adj

StyleShield: Exposing the Fragility of AIGC Detectors through Continuous Controllable Style Transfer

arXiv:2605.00924v1 Announce Type: new Abstract: AI-generated content (AIGC) detectors are increasingly deployed in high-stakes settings such as academic integrity screening, yet their reliability rest