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arXiv:2609.16933v1 Announce Type: cross Abstract: Modern predictive systems expose multiple quantities that are commonly interpreted as measures of confidence. However, these quantities can summarize

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When majority rules, minority loses: bias amplification of gradient descent

DGX agent

arXiv:2505.13122v3 Announce Type: replace-cross Abstract: Despite growing empirical evidence of bias amplification in machine learning, its theoretical foundations remain poorly understood. We develop

safetyarxiv-cs-ai

16 Sept 2026

When Should LLMs Abstain? Chain-of-Self-Questioning for Selective Risk Control

arXiv:2609.17516v1 Announce Type: cross Abstract: Large language models can produce fluent answers when their factual support is weak. This paper introduces Chain-of-Self-Questioning (CoSQ), a prompt-

researcharxiv-cs-ai

Where Post-Training Quantization Breaks Text Embedders: A Measured Map Across Four Embedder Families

arXiv:2609.16391v1 Announce Type: cross Abstract: Weight-only post-training quantization is the cheapest way to shrink a retrieval embedder, and the received advice for applying it -- protect the embe

Where Should a Document Live: Context, Representations, or Parameters?

model-releasesarxiv-cs-ai

arXiv:2609.17346v1 Announce Type: cross Abstract: To answer questions outside of their pre-training data, large language models (LLMs) need access to new information, which can be presented in the con

Where Should the KV Cache Live? Placement Policies Across GPU, CPU, and SSD for Long-Lived Sessions

arXiv:2609.16215v1 Announce Type: new Abstract: GPU high bandwidth memory is scarce and expensive, and KV caches consume much of it as chats, agent loops, and document question answering accumulate st

safetyarxiv-cs-ai

Which Pretext Task Transfers? Self-Supervised Pretraining Objectives for Lung Ultrasound

arXiv:2609.16551v1 Announce Type: new Abstract: Self-supervised learning (SSL) can reduce the need for labelled medical images, but the choice of pretext objective remains unclear for lung ultrasound

researcharxiv-cs-cv

WholeBodyWAM: Generalizing Pre-trained World-Action Priors to Humanoid Loco-Manipulation via WBC-Grounded Coordination

arXiv:2609.16644v1 Announce Type: new Abstract: World Action Models (WAMs) offer a promising approach to general-purpose robot manipulation by jointly modeling visual dynamics and actions. However, mo

applicationsarxiv-cs-ro

Local Ai

Window-Diffusion: Accelerating Diffusion Language Model Inference with Windowed Token Pruning and Caching

arXiv:2601.20332v3 Announce Type: replace Abstract: Diffusion language models (DLMs) generate text through iterative denoising, but inference requires full-sequence attention at every iteration, resul

local-aiarxiv-cs-lg

World-Action Models for Robot Learning and Control: A Survey

arXiv:2609.16074v1 Announce Type: cross Abstract: Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts. Beyond mapping observations an

safetyarxiv-cs-cv

World Model Science: Self-Organized Criticality, Weak Chaos, and Metastable Belief Dynamics in Long-Horizon LLM Agents

model-releasesarxiv-cs-ai

arXiv:2609.17419v1 Announce Type: new Abstract: Long-horizon LLM agents must maintain task state across extended sequences of observations, actions, tool calls, and intermediate beliefs. We study thes

World Models for Embodied Intelligence: From Plausible to Controllable to Actionable

arXiv:2609.16697v1 Announce Type: cross Abstract: World models connect perception and decision-making in embodied intelligence by maintaining hidden state, anticipating consequences, comparing interve

XPACE: Joint World and Action Modeling from Heterogeneous Experience

arXiv:2609.17372v1 Announce Type: new Abstract: A general-purpose robot needs to draw on diverse experience, choose actions, and anticipate how those actions will change the world. We introduce XPACE,

safetyarxiv-cs-ro

XRoboToolKit-T: Teleoperation with High Stability and Precision with Tactile Sensing for Contact-rich Manipulation

arXiv:2609.16437v1 Announce Type: new Abstract: Collecting high-quality robot data for contact-rich manipulation tasks is essential for enabling robots to acquire real-world skills. However, existing

applicationsarxiv-cs-ro

You Don't Need To Train: Agentic Heuristic Learning Studio for Executable Human Activity Recognition

model-releasesarxiv-cs-ai

arXiv:2609.16065v1 Announce Type: cross Abstract: Human activity recognition (HAR) is usually framed as gradient-based training of neural networks. Agentic Heuristic Learning (AHL) Studio explores a c

Z-Loss Backward Geometry in Dense Output Heads and Sparse Routers

model-releasesarxiv-cs-cl

arXiv:2609.16179v1 Announce Type: cross Abstract: Z-loss has been widely applied to the logits of language-model output heads and sparse mixture-of-experts routers. Z-loss constrains the softmax log-n

Zero-shot narrative detection in social messaging

arXiv:2609.17310v1 Announce Type: new Abstract: This study investigates the zero-shot ability of large language models (LLMs) to identify and classify hidden narratives in social messages. Our researc

3D Gait-Based Autism Classification Using Attention-Enhanced Deep Learning with Cross-Fold Statistical Stability Analysis

model-releasesarxiv-cs-cv

arXiv:2609.14159v1 Announce Type: new Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose early diagnosis remains challenging because conventional clinical assessments are

A 25-mus/inf Event-driven Graph Neural Network Processor with Spatiotemporal Caching and Spline Convolution for Ultra-low-latency AI at the Edge

arXiv:2609.15241v1 Announce Type: new Abstract: Dynamic-vision-sensor (DVS) cameras generate events on a per-pixel basis with a mus-level temporal resolution, calling for new algorithm-hardware co-des

researcharxiv-cs-cv

A Building as a Repository: KIR, a Typed Intermediate Representation for Agent-Authored Building Information Models

arXiv:2609.14578v1 Announce Type: new Abstract: Autonomous agents that author building information models need more than access to a host API. They need a representation of what they intended, what a

agentsarxiv-cs-cv

Tutorials

A Chosen Future Can Still Be Rewritten: Causal Writability in Video Models

arXiv:2609.15980v1 Announce Type: cross Abstract: When a video model generates physically incorrect motion, did it fail to learn the correct motion, or did it learn it but fail to use it? We show the

tutorialsarxiv-cs-cv

A Comprehensive Review of Multimodal Facial State Analysis: Tasks, Methods, and Resources

arXiv:2609.13255v1 Announce Type: new Abstract: Facial state analysis plays a crucial role in understanding human expressions, psychological modeling, and human computer interaction. Traditional unimo

researcharxiv-cs-cv

A Conservative OCR-Enabled Workflow for R214 Sodium Screening of South African Packaged Foods

arXiv:2609.15427v1 Announce Type: cross Abstract: Using food package images to monitor sodium and salt content against South Africa's R214 sodium limits is challenging when screening decisions require

applicationsarxiv-cs-ai

A Controlled Reevaluation of Coreference Resolution Models

arXiv:2404.00727v3 Announce Type: replace Abstract: All state-of-the-art coreference resolution (CR) models involve finetuning a pretrained language model. Whether the superior performance of one CR m

A Corpus-Aligned Uthmani-to-Standard Quranic Word Mapping and a Deterministic Recitation Validator

model-releasesarxiv-cs-cl

arXiv:2609.14967v1 Announce Type: new Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (I

A Cross Community Agenda for Speech AI

arXiv:2609.13168v1 Announce Type: cross Abstract: Speech AI, any AI system that recognizes, transforms, or generates speech, is built and evaluated across two communities with only a small overlap: te

A derivative-fidelity failure mode in physics-informed neural networks: strengthened benchmark evidence from function-value training

arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values

A family of spectral conjugate gradient algorithms derived by least-squares approximations based on a modified quasi--Newton update with application to a revised robust binary classification model

arXiv:2609.13526v1 Announce Type: cross Abstract: We develop a spectral three-term modification of the classic Hestenes--Stiefel conjugate gradient algorithm, preserving its anti-jamming characteristi

A Few Pages of Markdown: Committed AI Configuration and Lower Quality Cost after Coding-Agent Adoption

arXiv:2608.25241v2 Announce Type: replace-cross Abstract: Coding agents increase development velocity but also technical debt. Prior work reports only average effects across adopters, hiding wide diff

A Functional SVD Framework for Regularized Multivariate Functional PCA with Dual Penalization

arXiv:2609.14815v1 Announce Type: cross Abstract: This paper introduces a novel framework for Regularized Multivariate Functional Principal Component Analysis (ReMFPCA) via Functional Singular Value D

A Game-Theoretic Framework for Incentive-Compatible AI training Under Renewable-Energy Constraints

arXiv:2609.15389v1 Announce Type: cross Abstract: As artificial intelligence systems increasingly rely on distributed and collaborative training, the energy footprint of these processes becomes a shar

agentsarxiv-cs-lg

A Generative AI Integrated Multimodal Framework for Low-Latency Multi-Camera Person Re-Identification

arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chang

researcharxiv-cs-ai

A Hybrid Agentic AI Framework for Intelligent Supply Chain Analytics

arXiv:2609.13561v1 Announce Type: new Abstract: Efficient utilization of supply chain analytics for decision making remains a significant challenge for planners, as critical tasks such as database que

A Hybrid Dependency-Aware Framework for Task Decomposition and Dynamic Agent Generation in Oracle-to-PostgreSQL Migration

arXiv:2609.14413v1 Announce Type: cross Abstract: Large language model (LLM)-based database migration is often treated as direct code transformation, although enterprise Oracle systems contain heterog

A Hybrid Hierarchical 1D-CNN-BiLSTM Framework for Extractive Summarization of Biomedical and Clinical Text

arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biom

A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis

arXiv:2609.15740v1 Announce Type: cross Abstract: Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-e

safetyarxiv-cs-ai

A latent dimension of Condorcet's jury theorem for multiple AI advisers

arXiv:2609.14438v1 Announce Type: cross Abstract: When the same question is asked of multiple AI advisers, as in self-consistency and LLM-as-a-judge panels, Condorcet's jury theorem predicts that addi

researcharxiv-cs-ai

A Lifecycle Cost Analysis of Smart-Contract-Coordinated Federated Learning Marketplaces

arXiv:2609.13170v1 Announce Type: cross Abstract: Blockchain-enabled Federated Learning (FL) marketplaces enable collaborative model training among mutually distrustful participants through smart cont

researcharxiv-cs-lg

A Machine Learning API for Earth Observation Data Cubes Based on openEO

arXiv:2609.13453v1 Announce Type: new Abstract: Earth Observation (EO) data are increasingly organized as spatio-temporal data cubes, while machine learning (ML) methods operate on tabular feature mat

researcharxiv-cs-lg

A Machine Learning Framework for Fault Detection, Isolation, and Severity Prediction of Autonomous VTOL Aircraft

arXiv:2609.14180v1 Announce Type: new Abstract: Fault detection in autonomous VTOL aircraft is critical because even minor component degradations can rapidly destabilize multirotor vehicles operating

safetyarxiv-cs-lg

A Multi-Resolution Multi-Domain Pre-Training Framework for Universal Traffic Forecasting

arXiv:2609.13878v1 Announce Type: new Abstract: Spatio-temporal traffic data are central to intelligent transportation systems, yet their heterogeneity poses significant challenges for large-scale mod

A Multi-Stage Agentic Framework for Effective Counter-Narrative Generation and Refinement

arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po

safetyarxiv-cs-cl

A New Transformer-Based Approach for Audio-Based Kinship Verification and a New Uncontrolled Mandarin Kinship Speech Dataset

arXiv:2609.14145v1 Announce Type: cross Abstract: Kinship verification is a task involving determining whether two individuals share a first-order kin relation. To tackle this task, we propose CONVTRA

applicationsarxiv-cs-ai

A note on goal-based hierarchical RL

arXiv:2609.14605v1 Announce Type: new Abstract: The agent-centric general value function (ACGVF) construction of itet{tasse2026goal} lets the agent make two decisions that are normally imposed by the

safetyarxiv-cs-ai

A Novel Robot-Assisted Learning Pedagogy for Children with ASD

arXiv:2609.14710v1 Announce Type: new Abstract: Interaction paradigms used in robot-assisted autism intervention have historically employed robots as teachers, clinical assistants, or more-abled peers

researcharxiv-cs-ro

A parameter-efficient three-branch architecture for multimodal misinformation detection with limited annotations

model-releasesarxiv-cs-cv

arXiv:2512.20257v2 Announce Type: replace Abstract: With the rise of easily accessible generative tools for creating and manipulating multimedia content, the threat of realistic synthetic alterations

A Personalized Dynamic Balance Evaluation Paradigm for Hip Exoskeleton-Assisted Walking under Unexpected Ground Perturbations

arXiv:2609.14765v1 Announce Type: cross Abstract: Hip exoskeletons may improve recovery from unexpected gait perturbations, yet personalizing assistance remains difficult because balance is multidimen

researcharxiv-cs-lg

A primer on evaluation methods for large language models in healthcare

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and