applications

Not to get too annoying about it but its worth noting that many of the 5,000 people at the labs with access to advanced model still haven't …

applicationsethan-mollick--x

Not to get too annoying about it but its worth noting that many of the 5,000 people at the labs with access to advanced model still haven't used them to their full extent: its all cybersecurity & math

11 Oct 2026

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Applications

The hidden tax on enterprise AI: Why data architecture is the ROI problem nobody budgeted for

DGX agent

Many large companies have spent the past few years investing in artificial intelligence infrastructure, software and implementation. Boards approved the plans. Finance built the business cases. Procur

applicationssiliconangle

11 Oct 2026

Not only did Astra beat Montezuma's Revenge, but so did Opus 5 But one of the criteria to resolve this AGI bet is for AI to win a discontinu…

applicationsethan-mollick--x

Not only did Astra beat Montezuma's Revenge, but so did Opus 5 But one of the criteria to resolve this AGI bet is for AI to win a discontinued prize that was sort of like a weak Turing Test. So Metacu

10 Oct 2026

Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception

arXiv:2610.11591v1 Announce Type: new Abstract: Robot navigation commonly uses wide-coverage, high-frequency sensing to reduce partial observability; this reliance becomes restrictive when another tas

Adaptive Adversarial Augmentation for Controllable Face Synthesis

arXiv:2610.11356v1 Announce Type: new Abstract: Synthetic data provides a scalable alternative to real-world datasets for training face recognition models, particularly under challenging conditions su

Adaptive Multi-Discriminator WGAN Framework for Resource-Constrained Internet of Vehicles Using Reinforcement Learning and Game Theory

arXiv:2610.10926v1 Announce Type: new Abstract: Managing machine learning workloads as a network service introduces a resource-orchestration problem distinct from conventional model training; which no

AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems

arXiv:2509.02302v2 Announce Type: replace Abstract: We study history-dependent online problems with a possibly inaccurate prediction of the future request sequence. Motivated by several real-world app

AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done b

AI-Mediated Self: How HCI Defines and Relates to the Self

arXiv:2610.10770v1 Announce Type: cross Abstract: How might AI alter how we understand and experience the self? This scoping review analyzes 102 papers to examine how the self is defined in the field

Automated Assembly Instruction Generation from CAD Models Using Grounded Large Language Models: A Human-in-the-Loop Framework

arXiv:2610.11896v1 Announce Type: new Abstract: Assembly documentation is a downstream manufacturing artifact that is still usually authored by interpreting CAD models by hand. Structured product data

Cited but Not Consulted: A Counterfactual Audit of Legal Chain-of-Thought Faithfulness

arXiv:2610.12361v1 Announce Type: new Abstract: Large language models increasingly justify legal decisions by naming the statute or precedent behind a verdict, treated as evidence that the decision fo

Coefficient Calibration as Selection Pressure in Symbolic Regression

arXiv:2610.10931v1 Announce Type: new Abstract: In memetic symbolic regression, candidate structures are compared after coefficient calibration, so the calibration protocol itself contributes to evolu

Cognition-Oriented Emotion Tracing from Causes to Consequences in Real-World Social Scenes

arXiv:2610.11410v1 Announce Type: new Abstract: Affective computing has progressed from categorical emotion recognition to open-ended affective analysis with large multimodal models. Yet affective sci

Conditional Kernel Stein Discrepancy

arXiv:2610.11863v1 Announce Type: cross Abstract: Kernel Stein discrepancies (KSDs) provide a versatile tool for comparing distributions. One of their main applications is in quantifying the goodness-

Distributed Relative Localization for Homogeneous Multi-Robot Systems through UWB Ranging and Limited Communications

arXiv:2610.11308v1 Announce Type: new Abstract: Accurate and reliable relative localization is crucial for multi-robot applications like exploration, search, and rescue missions. LiDAR-based solutions

DLC: A Metric-Guided Dynamic Loss Controller for Multi-Objective Training

arXiv:2610.11433v1 Announce Type: new Abstract: In this paper, we introduce a metric-guided dynamic loss controller (DLC) for multi-objective image restoration. Conventional image restoration pipeline

DOGS: Design-Space Sampling for Prompt-Driven Logo Generation

arXiv:2610.10760v1 Announce Type: new Abstract: Prompt optimization for text-to-image (T2I) generation has been pursued almost entirely as text rewriting, in which a short user brief is expanded into

EgoVoice: Proactive Spoken Assistance from Egocentric Multimodal Streams

arXiv:2610.12248v1 Announce Type: new Abstract: Wearable augmented reality (AR) assistants are moving toward continuous real-world interaction, where they perceive the user's activity through first-pe

applicationsarxiv-cs-cl

Experience-Guided Initiation Search for Learned Skills in Skill Composition

arXiv:2610.11418v1 Announce Type: new Abstract: Deploying frozen learned skills, such as Vision-Language-Action (VLA) policies, in new environments requires identifying initiation configurations that

HANS: A Handwritten Answer Sheet Dataset for Noisy Hybrid Document Parsing

arXiv:2610.12363v1 Announce Type: new Abstract: Intelligent grading and automated scoring technologies constitute critical infrastructure for smart education. However, existing document parsing and ha

HarnessSQL: Harness-Native Training for SQL Agents in Realistic Database Environments

arXiv:2610.12274v1 Announce Type: new Abstract: Text-to-SQL models are commonly trained to map questions directly to static queries, whereas real-world database agents operate through stateful, multi-

applicationsarxiv-cs-cl

How Firm Should a Grasp Be?

arXiv:2610.11221v1 Announce Type: cross Abstract: An ideal robot grasp is firm enough to securely handle an object, yet gentle enough to avoid damaging it. Achieving this balance requires knowledge of

ICYMI: What landed for AI builders in September 2026

A monthly recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026: broader model choice, faster serverless agents with built-in evaluation, and automated

applicationsaws-ml-blog

Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection?

arXiv:2610.12167v1 Announce Type: new Abstract: Generalist graph anomaly detection (GAD) aims to build a foundation model that detects anomalies on arbitrary unseen graphs without retraining or fine-t

ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

arXiv:2610.12213v1 Announce Type: cross Abstract: Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Proc

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

Masked Generative Motion Planning with Geometry-Guided Token Search

arXiv:2610.10646v1 Announce Type: cross Abstract: Generative motion planners typically use learned trajectory priors for initial generation, while leaving test-time repair to local continuous refineme

Multimodal Large Language Models as Image Classifiers

arXiv:2603.06578v3 Announce Type: replace Abstract: Multimodal Large Language Model (MLLM) classification performance depends critically on evaluation protocol and ground truth quality. Studies compar

PhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization

arXiv:2603.13228v3 Announce Type: replace-cross Abstract: Recent progress in text-conditioned human motion generation has been largely driven by diffusion models trained on large-scale human motion da

Randomized trials with old GPT-4o: 'AI access raises test scores, and a smaller gain persists a week later. Gains remain for students who us…

applicationsethan-mollick--x

Randomized trials with old GPT-4o: 'AI access raises test scores, and a smaller gain persists a week later. Gains remain for students who use AI as a tutor (“augmentation”) and fade for students who h

Recovery Guarantees for Posterior Sampling of One-Bit Compressed Sensing

arXiv:2610.11834v1 Announce Type: new Abstract: We study the sample complexity of noisy one-bit compressed sensing for signals drawn from a prior distribution. By characterizing the effective distribu

Rewiring Semantics, Dynamics, and Control: A Simple yet Effective Action-Centric Tri-Stream Transformer

arXiv:2610.11416v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent framework for complex robotic manipulation, building on the strong semantic understand

RoboRSI: Stable, efficient, and reusable robot self-evolution in complex real-world environments

arXiv:2610.12424v1 Announce Type: cross Abstract: A generalist robot should not only perform diverse tasks but also improve through experience, turning what it learns during execution into capabilitie

SafeInferCom: Safe Inference-Time Compute via Verifier-Guided Mid-Generation Intervention for Robotic Task Planning

arXiv:2610.11223v1 Announce Type: cross Abstract: Large Reasoning Language Models (LRLMs) enable multi-step reasoning for robotic task planning, but continued reasoning can overwrite valid intermediat

Same Action, Different Outcome: Variability in Dynamic Cloth Manipulation

arXiv:2610.10801v1 Announce Type: new Abstract: Although cloth is known to exhibit different outcomes under repeated fast dynamic motions, even when the same trajectory is applied, this variability ha

Seed2Scale: A Self-Evolving Data Engine with Parallel Worlds Expansion for Scalable Robot Learning

arXiv:2603.08260v2 Announce Type: replace Abstract: Existing data generation methods for robot learning suffer from limited exploration, embodiment gaps, low signal-to-noise ratios, and domain shifts,

Skeleton-Guided Progressive Test-Time Adaptation for Thin Curvilinear Structures

arXiv:2610.11104v1 Announce Type: new Abstract: Accurate segmentation of thin curvilinear structures is vital for various real-world applications, from vessel analysis to road extraction. Yet their in

Sources: top execs at Anthropic, OpenAI, and others are gaming out scenarios for a public and political revolt following a catastrophic AI event (Maria Curi/Axios)

Maria Curi / Axios: Sources: top execs at Anthropic, OpenAI, and others are gaming out scenarios for a public and political revolt following a catastrophic AI event — - The first example of significan

applicationstechmeme

SPAN-Nav: Generalized Spatial Awareness for Versatile Embodied Navigation

arXiv:2603.09163v2 Announce Type: replace Abstract: Recent embodied navigation approaches leveraging Vision-Language Models (VLMs) demonstrate strong generalization in versatile Vision-Language Naviga

Stochastic Grouping Conformal Prediction for Effective Subgroup Reliability

arXiv:2610.11957v1 Announce Type: cross Abstract: Conformal prediction offers a distribution-free coverage guarantee, making it especially attractive for clinical applications. Standard conformal pred

Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives

arXiv:2610.11734v1 Announce Type: cross Abstract: We introduce Timer-M1, a pretrained multivariate time series foundation model that learns with primitives for zero-shot forecasting. Across domains, t

Towards Scalable Meta-Learning of near-optimal Interpretable Models via Synthetic Model Generations

arXiv:2511.04000v2 Announce Type: replace-cross Abstract: Decision trees are widely used in high-stakes fields like finance and healthcare due to their interpretability. This work introduces an effici

Trust, Don't Trust, or Flip: Robust Preference-Based Reinforcement Learning with Multi-Expert Feedback

arXiv:2601.18751v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise traject

UniData: Universal Multimodal Instruction Generation Pipeline

arXiv:2610.11363v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly being applied in a wider range of real-world scenarios. However, due to the substantial labor

UNITAS: A 3D-Native World Action Model for Embodied Manipulation

arXiv:2610.12099v1 Announce Type: new Abstract: World action models (WAMs) aim to answer a coupled physical question: given a task instruction, what motion should the robot execute, and how will that

Warehouse robotics startup Ultra raised a 12M seed and a 50M Series A, and expands its deal with Physical Intelligence to supply AI software for its robots (Jeff John Roberts/Fortune)

Jeff John Roberts / Fortune: Warehouse robotics startup Ultra raised a 12M seed and a 50M Series A, and expands its deal with Physical Intelligence to supply AI software for its robots — Finance edito

applicationstechmeme

A Review Of Robotic World Models For Dynamic Environments Based On Factor And Scene Graphs

arXiv:2610.08800v1 Announce Type: cross Abstract: Models based on graphs have emerged in robotics as a powerful foundation for internal world representations, where factor and scene graphs are among t

8 Oct 2026

Beyond Reward Suppression: Near-Optimal Offline Attacks on Warm-Start Bandits with Bounded Rewards

arXiv:2610.10000v1 Announce Type: new Abstract: Adversarial attacks on bandits aim to mislead a learner toward a target arm while keeping the attack cost small. Existing attacks typically achieve this