Search: “inference”

Cognitive Twins: Investigating Personalized Thinking Model Building and Its Performance Enhancement with Human-in-the-Loop

model-releasesarxiv-cs-lg

arXiv:2605.04761v1 Announce Type: new Abstract: This paper presents the Personalized Thinking Model (PTM), a hierarchical and interpretable learner representation designed for AI supported education.

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Model Releases

ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation

DGX agent

arXiv:2605.05126v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models primarily focus on mapping 2D observations to actions, but exhibit notable limitations in spatiotemporal per

model-releasesarxiv-cs-ro

7 May 2026

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models

arXiv:2605.05204v1 Announce Type: new Abstract: The landscape of high-performance image generation models is currently shifting from the inefficient multi-step ones to the efficient few-step counterpa

Denoising Particle Filters: Learning State Estimation with Single-Step Objectives

arXiv:2602.19651v2 Announce Type: replace-cross Abstract: Learning-based methods commonly treat state estimation in robotics as a sequence modeling problem. While this paradigm can be effective at max

Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework

arXiv:2605.04079v1 Announce Type: new Abstract: Early and reliable detection of Alzheimer's disease (AD) is crucial for timely clinical intervention and improved patient management. It also supports t

Elicitation Matters: How Prompts and Query Protocols Shape LLM Surrogates under Sparse Observations

arXiv:2605.04764v1 Announce Type: new Abstract: Large language models are increasingly used as surrogate models for low-data optimization, but their optimizer-facing prediction and its uncertainty rem

safetyarxiv-cs-cl

Encoding Predictability and Legibility for Style-Conditioned Diffusion Policy

arXiv:2603.16368v2 Announce Type: replace-cross Abstract: Striking a balance between efficiency and transparent motion is a core challenge in human-robot collaboration, as highly expressive movements

safetyarxiv-cs-lg

Applications

FideDiff: Efficient Diffusion Model for High-Fidelity Image Motion Deblurring

arXiv:2510.01641v3 Announce Type: replace Abstract: Recent advancements in image motion deblurring, driven by CNNs and transformers, have made significant progress. Large-scale pre-trained diffusion m

applicationsarxiv-cs-cv

FMI_SU_Yotkova_Kastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals

arXiv:2605.04157v1 Announce Type: new Abstract: SemEval-2026 Task 13 investigates machine-generated code detection across multiple programming languages and application scenarios, asking participating

researcharxiv-cs-cl

Tutorials

From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation

arXiv:2605.04590v1 Announce Type: new Abstract: Text-based image segmentation aims to delineate object boundaries within an image from text prompts, offering higher flexibility and broader application

tutorialsarxiv-cs-cv

Gyan: An Explainable Neuro-Symbolic Language Model

arXiv:2605.04759v1 Announce Type: new Abstract: Transformer based pre-trained large language models have become ubiquitous. There is increasing evidence to suggest that even with large scale pre-train

researcharxiv-cs-cl

Hardware-Aware Neural Feature Extraction for Resource-Constrained Devices

arXiv:2605.04282v1 Announce Type: new Abstract: Visual SLAM is a core component of spatial computing systems, yet deploying learned local feature extractors on microcontroller-class hardware remains c

local-aiarxiv-cs-lg

HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction

arXiv:2605.04682v1 Announce Type: cross Abstract: Spatial transcriptomics offers spatially resolved gene expression profiling within tissue sections, but its cost and limited throughput hinder large-s

local-aiarxiv-cs-cv

Ilov3Splat: Instance-Level Open-Vocabulary 3D Scene Understanding in Gaussian Splatting

arXiv:2605.04506v1 Announce Type: new Abstract: We introduce Ilov3Splat, a novel framework for instance-level open-vocabulary 3D scene understanding built on 3D Gaussian Splatting (3D-GS). Most prior

researcharxiv-cs-cv

InSpatio-WorldFM: An Open-Source Real-Time Generative Frame Model

arXiv:2603.11911v3 Announce Type: replace Abstract: We present InSpatio-WorldFM, an open-source real-time frame model for spatial intelligence. Unlike video-based world models that rely on sequential

researcharxiv-cs-cv

Kinematic Discriminants of Deceleration Behavior Modes in Car-Following: Evidence from NGSIM Trajectory Data

arXiv:2605.05050v1 Announce Type: cross Abstract: Gap-closing rate and visual looming swap discriminative dominance depending on deceleration intensity - a finding that reconciles a long-standing conf

agentsarxiv-cs-lg

Hardware

Lambda closes $1 billion senior secured credit facility to meet gigawatt-scale AI infrastructure demand

Lambda Labs secured a $1 billion senior secured credit facility to fund the expansion of its AI infrastructure and meet growing demand for gigawatt-scale computational resources. This financing enable

hardwarelambda-labs

Model synthesis and identifiability analysis of stiff chemical reaction systems with inVAErt networks

arXiv:2605.04134v1 Announce Type: new Abstract: We consider the problem of learning data-driven replicas for stiff systems of ordinary differential equations arising in chemical kinetics that can be e

MuCALD-SplitFed: Causal-Latent Diffusion for Privacy-Preserving Multi-Task Split-Federated Medical Image Segmentation

arXiv:2605.04108v1 Announce Type: new Abstract: Federated Learning enables decentralized training by aggregating model updates across clients without sharing raw data, while Split Federated Learning f

researcharxiv-cs-cv

Tutorials

Multi Language Models for On-the-Fly Syntax Highlighting

arXiv:2510.04166v2 Announce Type: replace-cross Abstract: Syntax highlighting is a critical feature in modern software development environments, enhancing code readability and developer productivity.

tutorialsarxiv-cs-ai

Multiscale Euclidean Network Trajectories: Second-Moment Geometry, Attribution, and Change Points

arXiv:2605.04589v1 Announce Type: cross Abstract: A central challenge in dynamic network analysis is to represent temporal evolution in a way that is both geometrically meaningful and statistically id

NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise

arXiv:2605.04313v1 Announce Type: new Abstract: Causal reasoning in natural language requires identifying relevant variables, understanding their interactions, and reasoning about effects and interven

ReflectDrive-2: Reinforcement-Learning-Aligned Self-Editing for Discrete Diffusion Driving

arXiv:2605.04647v1 Announce Type: new Abstract: We introduce ReflectDrive-2, a masked discrete diffusion planner with separate action expert for autonomous driving that represents plans as discrete tr

local-aiarxiv-cs-ro

RemoteZero: Geospatial Reasoning with Zero Human Annotations

arXiv:2605.04451v1 Announce Type: new Abstract: Geospatial reasoning requires models to resolve complex spatial semantics and user intent into precise target locations for Earth observation. Recent pr

agentsarxiv-cs-cv

Revisiting the Travel Planning Capabilities of Large Language Models

arXiv:2605.03308v1 Announce Type: new Abstract: Travel planning serves as a critical task for long-horizon reasoning, exposing significant deficits in LLMs. However, existing benchmarks and evaluation

agentsarxiv-cs-ai

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization

arXiv:2605.04539v1 Announce Type: new Abstract: Direct Preference Optimization (DPO), the efficient alternative to PPO-based RLHF, falls short on knowledge-intensive generation: standard preference si

ROCm Status in mid 2026 [D]

researchr-machinelearning

ROCm has reached production-ready status for PyTorch and vLLM workloads in 2026. PyTorch runs well and MI300X benchmarks are competitive, though the ecosystem gap with CUDA remains real. AMD's MI355X

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

arXiv:2601.08623v2 Announce Type: replace Abstract: Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from

Scalable Multi Agent Diffusion Policies for Coverage Control

arXiv:2509.17244v2 Announce Type: replace Abstract: We propose MADP, a novel diffusion-model-based approach for collaboration in decentralized robot swarms. MADP leverages diffusion models to generate

safetyarxiv-cs-ro

Scalable Policy Maximization Under Network Interference

arXiv:2505.18118v2 Announce Type: replace-cross Abstract: Many interventions, such as vaccines in clinical trials or coupons in online marketplaces, must be assigned sequentially without full knowledg

safetyarxiv-cs-lg

Hardware

Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

In this post, you will learn how to secure reserved GPU capacity for short-term workloads using Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML and Amazon SageMaker training plans. Th

hardwareaws-ml-blog

Tutorials

Self-Improvement for Fast, High-Quality Plan Generation

arXiv:2605.03625v1 Announce Type: new Abstract: Generative models trained on synthetic plan data are a promising approach to generalized planning. Recent work has focused on finding any valid plan, ra

tutorialsarxiv-cs-ai

Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction

arXiv:2605.04221v1 Announce Type: new Abstract: Clinical named entity recognition from dental progress notes is challenging because documentation is highly unstructured, domain-specific, and often pri

Smart Passive Acoustic Monitoring: Embedding a Classifier on AudioMoth Microcontroller

arXiv:2605.03412v1 Announce Type: cross Abstract: Passive Acoustic Monitoring (PAM) is an efficient and non-invasive method for surveying ecosystems at a reduced cost. Typically, autonomous recorders

agentsarxiv-cs-ai

Temporal Structure Matters for Efficient Test-Time Adaptation in Wearable Human Activity Recognition

arXiv:2605.04617v1 Announce Type: new Abstract: Wearable human activity recognition (WHAR) models often suffer from performance degradation under real-world cross-user distribution shifts. Test-time a

The Shape of Beliefs: Geometry, Dynamics, and Interventions along Representation Manifolds of Language Models' Posteriors

arXiv:2602.02315v2 Announce Type: replace Abstract: Large language models (LLMs) form implicit beliefs (posteriors over latent variables) from prompts, but we lack a mechanistic account of how these b

Transformed Latent Variable Multi-Output Gaussian Processes

arXiv:2605.05133v1 Announce Type: new Abstract: Multi-Output Gaussian Processes (MOGPs) provide a principled probabilistic framework for modelling correlated outputs but face scalability bottlenecks w

UniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings

arXiv:2505.11815v2 Announce Type: replace Abstract: Current vision-language models have been explored for multi-modal embedding tasks like information retrieval. However, they face significant challen

Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging

model-releasesarxiv-cs-cv

arXiv:2605.05161v1 Announce Type: new Abstract: Zero-shot anomaly localisation via vision-language models (VLMs) offers a compelling approach for rare pathology detection, yet its performance is funda

A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion

arXiv:2605.03360v1 Announce Type: cross Abstract: We present A-CODE, a fully atomic unified one-stage protein co-design model that simultaneously refines discrete atom types and continuous atom coordi

A Few-Step Generative Model on Cumulative Flow Maps

arXiv:2605.03623v1 Announce Type: new Abstract: We propose a unified, few-step generative modeling framework based on cumulative flow maps for long-range transport in probability space, inspired by fl

local-aiarxiv-cs-lg

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

researcharxiv-cs-ai

Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

arXiv:2603.01486v2 Announce Type: replace Abstract: Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where conte

agentsarxiv-cs-ai

AHPA: Adaptive Hierarchical Prior Alignment for Diffusion Transformers

arXiv:2605.03317v1 Announce Type: new Abstract: Representation alignment has recently emerged as an effective paradigm for accelerating Diffusion Transformer training. Despite their success, existing

local-aiarxiv-cs-cv

AsymK-Talker: Real-Time and Long-Horizon Talking Head Generation via Asymmetric Kernel Distillation

arXiv:2605.02948v1 Announce Type: new Abstract: Recent advances in diffusion models have markedly enhanced the visual fidelity of audio-driven talking head generation. Nevertheless, existing methods a

Best way to generate AI images locally on AMD RX 9070 XT?

local-air-stablediffusion

The AMD Radeon RX 9070 XT supports local AI image generation with significant performance improvements, including up to 4.3x faster Stable Diffusion 1.5 and 3.1x faster SDXL 1.0 performance . Users ca

Applications

Boosting Team Modeling through Tempo-Relational Representation Learning

arXiv:2507.13305v2 Announce Type: replace Abstract: Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and Social Sciences. Although a variety of computationa

applicationsarxiv-cs-lg

Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging

arXiv:2605.02734v1 Announce Type: new Abstract: Learning to Defer (L2D) enables a model to predict autonomously or defer to an expert, but prior work largely assumes flat label spaces. We study the fi

safetyarxiv-cs-ai