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What Streaming Anomaly Detection Finds (and Misses) in Industrial Time Series

arXiv:2609.39232v1 Announce Type: cross Abstract: EDF relies on continuous monitoring of its power plants to detect anomalies as soon as they occur. Given the absence of a universally optimal streamin

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What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification

DGX agent

arXiv:2609.38420v1 Announce Type: cross Abstract: We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the infer

researcharxiv-cs-ai

1 Oct 2026

When a Flatness Proxy Is Not a Function: Robustness Certificates and Training Interventions

arXiv:2609.38540v1 Announce Type: new Abstract: A valid curvature upper bound need not justify either a robustness certificate or an intervention on an intrinsic predictor property. We demonstrate thi

When Can Text Replace Vision? Structural Bottlenecks in Diagram Reasoning

arXiv:2609.39142v1 Announce Type: new Abstract: Can structured text replace vision for diagram reasoning? A wrong answer after textualization can arise because the representation omits information the

When Integral Meets Decomposition: A Signal-Level Self-Supervised Feature Decompose Paradigm for Multi-Modal Image Fusion

arXiv:2609.39004v1 Announce Type: new Abstract: Multimodal image fusion (MMIF) aims to integrate complementary information from different modalities into a high-quality fused image and support downstr

When Reasoning Goes Astray: Attention Dynamics of Uncontrolled Reasoning

arXiv:2609.38817v1 Announce Type: new Abstract: Large reasoning models (LRMs) improve performance on complex tasks through extended reasoning, yet the same process can degenerate into redundant verifi

When the Right Answer Is Missing: An Arithmetic-Dependent Rejection Bottleneck in Jev

arXiv:2609.39496v1 Announce Type: cross Abstract: Typed decision models such as Jev offer an efficient alternative to generative LLMs in decision-making workflows by selecting directly from predefined

researcharxiv-cs-cl

Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

arXiv:2609.38274v1 Announce Type: new Abstract: The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive

researcharxiv-cs-cl

Which Tasks Survive Self-Supervised Learning?

arXiv:2609.38393v1 Announce Type: cross Abstract: Same-instance self-supervised learning (SSL) learns representations by enforcing consistency across two views of the same underlying instance. This pr

Whitening Improves Robustness to Spurious Correlations in Linear Probes

arXiv:2609.39177v1 Announce Type: new Abstract: Deep neural networks tend to rely on simple features that may be spurious and thus fail to generalize. We study this problem in the setting of linear pr

Who Owns That? Evaluating Ownership Intuitions in Large Language Models

arXiv:2609.39483v1 Announce Type: new Abstract: Ownership establishes rights over the use, control, and transfer of objects. Understanding these relations is essential for AI systems to interact appro

WinoTS: Wavelet-based Self-Distillation for Time Series Models

arXiv:2609.39337v1 Announce Type: cross Abstract: Self-supervised pre-training of time series models is currently dominated by next-token prediction and reconstruction objectives. In continuous-valued

X-Planner: Event-Structured Task Planning for Embodied Intelligence

arXiv:2609.25187v2 Announce Type: replace Abstract: Task planning bridges high-level instructions and executable behavior in long-horizon manipulation, yet modern Vision-Language-Action (VLA) systems

A Finslerian Approach for Embedding Directed Data

arXiv:2609.37649v1 Announce Type: cross Abstract: Many datasets carry an intrinsic directionality: citations point backward in time, cells differentiate along lineages, and traffic follows preferred r

A Mesoscopic View of Transformer Weights Through Row and Column Scale Fields

arXiv:2609.35852v1 Announce Type: new Abstract: Pooled statistics of Transformer weights obscure how magnitude is distributed across functional channels, while individual weights are too numerous to c

A neural network that maintains and retrieves memories based on context

arXiv:2609.37791v1 Announce Type: new Abstract: Every day, people continuously infer situational context and adjust the way they understand and remember the world. Context, signaled by the prefrontal

A robust single-sensing-element tactile sensor for concurrent pressure and tackiness detection with real-time signal decoupling capability

arXiv:2609.36558v1 Announce Type: new Abstract: Integrating tackiness sensation into the artificial skin of humanoid robots significantly enhances their cognitive and operational capabilities. However

researcharxiv-cs-ro

A Sharp Transition in Data Reconstruction under Differential Privacy

arXiv:2609.37344v1 Announce Type: cross Abstract: Data reconstruction attacks have empirically been successful in recovering training samples from learned models, raising privacy concerns and motivati

A theoretical model of dynamical grammatical gender shifting based on set-valued set function

arXiv:2603.03510v3 Announce Type: replace-cross Abstract: This study investigates the diverse characteristics of nouns, focusing on both semantic (e.g., countable/uncountable) and morphosyntactic (e.g

Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation

arXiv:2508.17171v3 Announce Type: replace Abstract: Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibr

Active Budget Can Kill Sensitivity: Diagnosing and Repairing TopK Sparse Autoencoder Reliability

arXiv:2609.37857v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly scaled to wider dictionaries to recover fine-grained structure from large language model activations. Howeve

Adam under Generalized Smoothness with Second-Moment-Type Stochastic Gradients

arXiv:2609.37787v1 Announce Type: new Abstract: Adam is widely observed to remain stable even when the objective deviates significantly from global smoothness. Under the generalized smoothness framewo

Adapting Linear-Time Architectures for Tabular In-Context Learning

arXiv:2609.36337v1 Announce Type: new Abstract: Tabular foundation models achieve strong performance by conditioning on labelled examples in context, but softmax attention limits their use on large da

ADMM-based Continuous Trajectory Optimization in Graphs of Convex Sets

arXiv:2603.11335v2 Announce Type: replace Abstract: This paper presents a numerical solver for computing continuous trajectories in non-convex environments. Our approach relies on a customized impleme

researcharxiv-cs-ro

AESplat: Advancing Pose-Free Feed-Forward 3D Gaussian Splatting via Decoupled Appearance Modeling

arXiv:2609.36693v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) has demonstrated remarkable potential for generalized novel view synthesis. However, existing method

AffectReveal: Event-Grounded Emotion Recognition Beyond Visual Appearances

arXiv:2609.36563v1 Announce Type: new Abstract: Visual emotion recognition commonly assumes that all evidence required for prediction is contained in the observed image or video. Yet the same visible

All Roads Lead to Rome: Flow-driven Multi-Anchor Exploration for Open-Environment Active 3D Mapping

arXiv:2609.36889v1 Announce Type: new Abstract: To advance the development of embodied intelligence, Open-Environment Active 3D Mapping has attracted increasing attention, aiming to perform a long-hor

researcharxiv-cs-ro

Alpha Diffusion Language Models: Factorization Alone Is Not the Problem

arXiv:2609.38066v1 Announce Type: new Abstract: Discrete diffusion language models can generate multiple tokens in parallel, but reducing the number of denoising steps can lead to inconsistent predict

AMU:Admission and Memory Update for Personalized Conversations---Structured Memory with SLM Guided Control

arXiv:2609.36976v1 Announce Type: new Abstract: Large language models (LLMs) have become the foundation of personalized assistants, but maintaining persistent user memory across long-term interactions

researcharxiv-cs-cl

An Effective, Reliable, and Robust Framework for Human Activity Recognition Using Wearable Sensors

arXiv:2609.36848v1 Announce Type: new Abstract: Human Activity Recognition (HAR) through wearable sensors greatly improves the quality of human life through its multiple applications. For HAR, multi-s

An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis

arXiv:2609.37941v1 Announce Type: new Abstract: This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constan

Aperture: Merge-Consistent Rotary States for Compressed Tokens

arXiv:2609.36781v1 Announce Type: new Abstract: Token compression combines content from several positions, yet rotary position embeddings usually assign the merged token one coordinate. We ask what po

Are In-Context Images Worth 10 Dimensions?

arXiv:2609.37659v1 Announce Type: new Abstract: There has been significant work on understanding the In-Context Learning capabilities of Large Language Models, especially on the induction circuit. For

ARGOS: Reinforcement Learning-Driven Multidimensional Elasticity for Service Orchestration in the Computing Continuum

arXiv:2609.37085v1 Announce Type: cross Abstract: Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited an

AS^2D: Accelerating On-Demand Audio Understanding on Mobile Devices

arXiv:2609.37617v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive generation by using a smaller drafter to propose tokens for batched verification by a larger target. H

ATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning

arXiv:2609.36333v1 Announce Type: cross Abstract: Latent world models rely on representation geometry for planning, yet regularizing the latent marginal alone does not determine the state-to-state rel

Attention-Scoped Guidance: Training-Free Spatial Control for Image Editing

arXiv:2609.37492v1 Announce Type: new Abstract: Instruction-guided image editing should change what the instruction names and leave the rest of the image untouched. In dual classifier-free guidance (C

Authority Before Utility: Non-Compensatory Control for Persistent LLM Memory

arXiv:2609.37474v1 Announce Type: new Abstract: Persistent memory creates a control problem that retrieval relevance alone does not solve: a memory can remain highly useful after an update, deletion,

Backdoor Mitigation in Decentralized LLM Fine-Tuning

arXiv:2609.37367v1 Announce Type: cross Abstract: Decentralized large language model (LLM) fine-tuning lets organizations collaboratively train a shared LLM on data they cannot pool, without a central

BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

arXiv:2406.00083v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge bases to

BarcodeMAE+: Rethinking Masked Pretraining and Global Representations for DNA Barcode Foundation Models

arXiv:2609.35877v1 Announce Type: cross Abstract: Many DNA foundation models are pretrained by masking parts of a sequence and asking the model to reconstruct them. Standard masked pretraining exposes

Behavioral Capacity Certificates for Quantized Language Models

arXiv:2609.37887v1 Announce Type: new Abstract: Activation and key-value cache precision change what a quantized language model computes without altering its stored weights. Direct weight-code bounds,

Behavioral Convergence Without Representational Convergence: Persistent Training-History Dependence in Neural Networks

arXiv:2609.37836v1 Announce Type: new Abstract: Neural networks trained toward the same final objective can reach similar predictive performance while retaining internal representations shaped by earl

Benchmarking Vision-Language Models on Synapse Detection and Proofreading in Connectomics

arXiv:2609.36492v1 Announce Type: cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse dete

Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning

arXiv:2609.36359v1 Announce Type: new Abstract: Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search. Its indices are constructed primarily based on ge

Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery

arXiv:2609.37263v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs) achieve remarkable success, hallucinations remain a significant barrier to their reliable deployment. Recent

Beyond Readability: Evaluating Task Information Recoverability

arXiv:2609.36957v1 Announce Type: new Abstract: Direct visual readability and task-information recoverability are different quantities. Failure to decode a target from a fixed observation need not eli

Beyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoods

arXiv:2609.37218v1 Announce Type: cross Abstract: Semantic watermarking improves robustness against watermark removal attacks by embedding detectable signals into sentence-level representations. Howev