Search: “concepts”

Autonomous thermodynamic cycles via robotic mobility and sensing

arXiv:2610.11667v1 Announce Type: cross Abstract: Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these

agentsarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

BiomedXPro: Prompt Optimization for Explainable Diagnosis with Biomedical Vision Language Models

DGX agent

arXiv:2510.15866v2 Announce Type: replace Abstract: The clinical adoption of biomedical vision-language models is hindered by prompt optimization techniques that produce either uninterpretable latent

safetyarxiv-cs-cv

9 Oct 2026

Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation

arXiv:2610.11067v1 Announce Type: new Abstract: Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classe

Digital Twin for Pre-Deployment Validation of AI-Driven Safety-Critical Industrial Edge Control Loops

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

safetyarxiv-cs-ro

DigitalOcean MicroVMs: Fast, isolated compute for your AI agent infrastructure

Coding-agent platforms, sandbox products, and code-execution services all need the same thing: isolated machines that start up fast, retain their state between bursts of work, and don’t consume comput

agentsdigitalocean

Enabling Preference-driven Unlearning in Few-step Distilled Text-to-Image Diffusion Models

arXiv:2610.10859v1 Announce Type: new Abstract: Text-to-image diffusion models are increasingly distilled into few-step variants and being deployed to enable fast inference. However, their ability to

safetyarxiv-cs-cv

Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention

arXiv:2610.11690v1 Announce Type: cross Abstract: In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing. The basic definit

From Retrieval to Reconstruction: Constructing Evolvable Cognitive Memory for Long-Term Dialogue

arXiv:2610.11314v1 Announce Type: new Abstract: Large Language Models (LLMs) serving as long-term dialogue agents require memory systems that support reliable reasoning over extended interactions. How

agentsarxiv-cs-cl

Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis

arXiv:2610.11025v1 Announce Type: cross Abstract: Exploratory data analysis (EDA) is rarely open-ended in practice: analysts work from high-level domain questions toward the concrete analyses that can

LinSlot: Exploiting Linear Representation hypothesis for unsupervised attribute discovery from slot based object representation

arXiv:2610.10722v1 Announce Type: cross Abstract: This paper studies the problem of learning disentangled representations of objects and their attributes from raw, unstructured image data. Slot-based

Multi-Bandwidth Distribution Matching Distillation: On the Equivalence of Distribution Matching Distillation and Drifting Models

arXiv:2610.10989v1 Announce Type: cross Abstract: Researchers are exploring effective one-step generative model continuously, and, Drifting Models (Deng et al., 2026), demonstrate great potential in o

Tabula Rasa: Monte Carlo estimation of unit-variance noise with controlled spatio-temporal correlation

arXiv:2610.11653v1 Announce Type: cross Abstract: We suggest a method to generate time-varying Gaussian noise with controlled variance and controlled temporal correlation. This noise is used in severa

The optimal information complexity of VC learning

arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori

ActiveLang: Active Open-Vocabulary 3D Mapping with Semantic-Uncertainty-Guided Exploration

arXiv:2610.09518v1 Announce Type: new Abstract: As robots increasingly assist humans with diverse tasks, they need both geometric and semantic understanding of their surroundings. Moreover, robots oft

agentsarxiv-cs-cv

Alice: A Large-Scale German Benchmark for Rubric-Based Multi-Dimensional Automatic Short Answer Scoring

model-releasesarxiv-cs-cl

arXiv:2610.09661v1 Announce Type: new Abstract: Automatic Short Answer Scoring (ASAS) is central to NLP for Education. However, openly available benchmarks remain scarce, and existing datasets largely

Align Before You Combine: Reference Space Calibration for Supervision Without Ground Truth

arXiv:2610.09525v1 Announce Type: new Abstract: We introduce a calibration-first framework that produces supervision scores without access to ground-truth labels or a shared annotation space. Our fram

Benchmarking Behavioral Steerability in Behavior Foundation Models

model-releasesarxiv-cs-ro

arXiv:2610.10198v1 Announce Type: new Abstract: Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve

Boosting and the Expressive Power of Simple Weak Learners via the gamma-VC Dimension

arXiv:2610.10383v1 Announce Type: new Abstract: Boosting converts weak hypotheses with a small edge over random guessing into highly accurate predictors, but the expressive power of the resulting clas

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

safetyarxiv-cs-cl

From Retrieval to Customer Context: Evaluating Frontier-Model Systems for Voice-of-Customer Analysis

arXiv:2610.09375v1 Announce Type: new Abstract: Organizations increasingly use frontier language models to analyze customer feedback, but answer quality also depends on how that feedback is organized

agentsarxiv-cs-lg

Applications

LeCuration: A Tiny World Model as a Data Curation Multi-Tool

arXiv:2610.09285v1 Announce Type: cross Abstract: Many applications of physical AI run within finite or closed physical worlds with a limited set of physical laws governing object behavior. Examples i

applicationsarxiv-cs-cv

Reasoning-Token Spikes Under Prompted Untruthful Responding in Large Language Models

arXiv:2610.10405v1 Announce Type: cross Abstract: Monitoring the chain-of-thought of reasoning artificial intelligence (AI) models remains a key approach to detecting deception and other forms of misb

researcharxiv-cs-cl

The Metagame of Interpretability and Meta-Attributions

arXiv:2605.06295v2 Announce Type: replace Abstract: How can an arbitrary attribution method be generalized from first principles to capture interactions? We answer this with the metagame, a conceptual

U-Space: Uncovering When and Why Uncertainty Arises in Language Models

arXiv:2610.09087v1 Announce Type: new Abstract: Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ig

researcharxiv-cs-cl

Unbounded Characteristic and Universal Kernels

arXiv:2610.09731v1 Announce Type: cross Abstract: Kernel methods are among the most powerful tools in machine learning and statistics, with a large number of successful applications. Their immense suc

A doctrine-grounded visual question answering dataset for Tactical Combat Casualty Care

arXiv:2610.07339v1 Announce Type: cross Abstract: Tactical Combat Casualty Care (TC3) requires responders to connect visual observations of injuries and interventions with established clinical guidanc

Local Ai

Algorithmically Aligned Neural Agglomerative Tree Construction

arXiv:2610.07271v1 Announce Type: new Abstract: Linkage algorithms for hierarchical clustering (HC) are a powerful and efficient framework for constructing clustering trees, yet it is often unclear wh

local-aiarxiv-cs-lg

Anytime-valid simulation-based hypothesis testing

arXiv:2610.08210v1 Announce Type: cross Abstract: For a given data distribution (X_t)_{t in N} sim Q i.i.d., we investigate the hypothesis testing problem: H_0: Q = P_0 vs. H_1: Q = P_1, for two diffe

Detecting a Shift Is Not Enough: Exact Minimax Limits of Linear Representation Repair

arXiv:2610.08069v1 Announce Type: new Abstract: A mean shift between two data sources can be easy to detect but hard to remove without substantially changing their representations. We cast its removal

tutorialsarxiv-cs-lg

Explore ideas through interactive visuals that respond as you learn, try, and discover.

On October 7, 2026 OpenAI released a session titled “Explore ideas through interactive visuals that respond as you learn, try, and discover.” The webcast showcased real‑time visual tools that adapt to

tutorialsopenai--x

Lineage-Aware Memory Governance: A Derivation-Gated Framework for Privacy-Preserving Column-Level Access Control in Enterprise AI Agents

arXiv:2610.07258v1 Announce Type: cross Abstract: Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results the requester

safetyarxiv-cs-ai

Machine Learning for German Redispatch Forecasting under Data Delays and Temporal Distribution Shift

arXiv:2610.08337v1 Announce Type: cross Abstract: Public redispatch records provide empirical data for grid congestion forecasting, but delayed reporting, zero-inflated distributions, and temporal shi

MedCORE: Criteria-Grounded Clinical Reasoning for Interpretable Medical Image Diagnosis

arXiv:2610.08528v1 Announce Type: cross Abstract: Clinical diagnosis is inherently a structured reasoning process, yet existing deep learning models often bypass this structure by mapping image featur

Optimization Encoders: Rethinking Second-Order Meta-Learning for Neural Fields

arXiv:2610.08075v1 Announce Type: cross Abstract: Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred f

safetyarxiv-cs-cv

Predicting kernel regression learning curves from only raw data statistics

arXiv:2510.14878v3 Announce Type: replace-cross Abstract: We study kernel regression with common rotation-invariant kernels on real datasets including CIFAR-5m, SVHN, and ImageNet. We give a theoretic

tutorialsarxiv-cs-ai

Local Ai

SAGE: Semantic Anchor-Guided Evolution for Grounded Medical QA Data Synthesis

arXiv:2610.08093v1 Announce Type: cross Abstract: Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the limited availability of high-qu

local-aiarxiv-cs-ai

Silicon Language: A Robot-Native Knowledge Exchange Framework for Heterogeneous Robots

arXiv:2610.07650v1 Announce Type: new Abstract: Reusing a capability across heterogeneous robots still requires substantial human adaptation and verification: transferring a skill often means re-engin

safetyarxiv-cs-ro

Supermarket Product Detection and Recognition: Utilizing Deep Learning with Rectified Imagery

arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.

UniPose9D: Universal Category-Agnostic Object Pose Estimation

arXiv:2607.09985v2 Announce Type: replace Abstract: Object pose estimation is a fundamental problem in 3D vision. Although recent state-of-the-art approaches achieve strong performance, generalization

What Does Frechet Distance Measure? A Directional Decomposition

arXiv:2610.05518v1 Announce Type: cross Abstract: The Frechet distance is a de facto standard for evaluating generative models across domains, appearing as FID for images and FVD for videos. It summar

safetyarxiv-cs-lg

WildMatch: Weakly Supervised Image Matcher Adaptation for Wildlife Re-Identification

arXiv:2610.07384v1 Announce Type: cross Abstract: Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query ima

tutorialsarxiv-cs-ai

Applications

A Taxonomy on Collective Awareness

arXiv:2610.06427v1 Announce Type: new Abstract: As robotic teams tackle increasingly complex tasks in dynamic and unstructured environments, effective coordination requires agents to maintain accurate

applicationsarxiv-cs-ro

AIProver: Agentic Auto-Formalization of Mathematical Research via Certificate-Driven Evolving Harness

arXiv:2610.05367v1 Announce Type: cross Abstract: Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verificati

Causally Fair Generation with Large Language Models

arXiv:2610.04444v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, complete, and transform information in settings where their outputs can shape conseque

safetyarxiv-cs-lg

CCQ: A Multi-State Child Care Quality Dataset to Support AI for Children's Health Research

arXiv:2610.05863v1 Announce Type: new Abstract: High-quality child care in early life is a critical determinant of children's growth and development. Research on child care quality has been constraine

DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management

arXiv:2603.19621v2 Announce Type: replace Abstract: Deep Reinforcement Learning (DRL) provides a general-purpose methodology for training inventory policies that can leverage big data and compute. How

safetyarxiv-cs-lg

Local Ai

Generative World Models Enable Predictive Control of Laser Melt Pool Dynamics

arXiv:2610.06250v1 Announce Type: new Abstract: World models, which learn how environments respond to actions, are emerging as a powerful paradigm for planning through imagined futures, transforming d

local-aiarxiv-cs-lg

Learning to Read the Contextual Tokens in Diffusion Transformers

arXiv:2610.06844v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) jointly process visual and textual representations throughout generation. These models repeatedly update the

safetyarxiv-cs-cv