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ILRR: Inference-Time Steering Method for Masked Diffusion Language Models

arXiv:2601.21647v2 Announce Type: replace Abstract: Discrete Diffusion Language Models (DLMs) offer a promising non-autoregressive alternative for text generation, yet effective mechanisms for inferen

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Implementation of Quantum Implicit Neural Representation in Deterministic and Probabilistic Autoencoders for Image Reconstruction/Generation Tasks

DGX agent

arXiv:2603.06755v3 Announce Type: replace Abstract: We propose a quantum implicit neural representation (QINR)-based autoencoder (AE) and variational autoencoder (VAE) for image reconstruction and gen

researcharxiv-cs-lg

22 Sept 2026

Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics

arXiv:2501.06762v4 Announce Type: replace-cross Abstract: Continuous adaptive learning, the ability to adapt to the environment and keep improving performance, is a hallmark of natural intelligence. B

Increasing Skill Level Recruits Deeper Attention Layers in a Frozen Chess Transformer

arXiv:2609.23917v1 Announce Type: cross Abstract: Chess involves complex reasoning in a deterministic environment, which makes it a useful setting for studying the mechanisms of computation inside tra

Infectious Bovine Pinkeye Detection Using Computer Vision and Imbalance-Aware Learning

arXiv:2609.23714v1 Announce Type: new Abstract: Infectious bovine pinkeye is a contagious ocular disease that adversely affects cattle health, welfare, and agricultural productivity. Conventional diag

INTCORT: Training-Free Spatial Reasoning Enhancement for Vision-Language Models via Input Transformations and Confidence Routing

arXiv:2609.24813v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in multimodal tasks, yet they still exhibit poor ability in spatial reasoning. E

Interpretable Multi-Hypersphere Deep Anomaly Detection for Open-set Supervised Anomaly Detection

arXiv:2609.23008v1 Announce Type: new Abstract: Multi-class open-set anomaly detection requires a model to characterize the normal acceptance domain formed by multiple heterogeneous subdistributions u

Interpretable Stress Detection from ECG Signals Using Motif-Based Anomaly Analysis

arXiv:2609.22179v1 Announce Type: cross Abstract: Stress detection using physiological signals has gained significant attention due to its impact on both physical and mental health. While existing app

Iterative Atom Refinement: A Monotonicity Principle for Dictionary Learning

arXiv:2609.23812v1 Announce Type: new Abstract: Dictionary learning seeks to recover an unknown dictionary A from observations {f y}_i = A{f x}_i with sparse coefficient vectors {f x}_i. We introduce

Jev for Scientific Decisions: Evaluating Semantic Choices and Their Consequences

arXiv:2609.24965v1 Announce Type: new Abstract: Scientific workflows often require choosing among known relations before a deterministic calculation can proceed. Whether observations share a culture,

Judging a Review by its Cover: A Reliability Analysis of LLM-based Peer Review Evaluation Metrics

arXiv:2609.23264v1 Announce Type: new Abstract: Peer-review evaluation is increasingly being automated with LLM-as-a-judge metrics, but this creates a measurement risk. A review may receive a high sco

Knowing, and Saying It Only When Asked: LLM Endognostics and the Schizognosis of Minerva-7B

arXiv:2609.22219v1 Announce Type: new Abstract: Evaluating an aligned language model by reading its answers assumes the answers carry the distinction the evaluator cares about. We introduce LLM endogn

KV-COBRA: KV Cache Compression via Co-Optimized Bit-Rank Allocation

arXiv:2609.24298v1 Announce Type: new Abstract: What limits KV-cache compression at extreme bit-rates? We argue that it is not the choice of compression scheme, but how its budget is allocated across

Label Propagation for Physics-Informed Neural Networks and Physics-Informed Gaussian Processes

arXiv:2404.05817v2 Announce Type: replace Abstract: We present a series of empirical results of the application of semi-supervised label propagation techniques in training physics-informed machine lea

Layer-Aware Position Embeddings for Visual Token Pruning in Multimodal Large Language Models

arXiv:2609.23715v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) incur substantial computational overhead due to the reliance on hundreds of visual tokens to represent images.

Layered e-skin for Shear Sensing

arXiv:2609.22493v1 Announce Type: new Abstract: This paper presents a stacked two-layer force-sensing resistor (FSR) array designed for robotic fingertips that combines high-resolution pressure mappin

LE4Mob: Towards Inductive, Distance-Aware and General-Purpose Location Embedding for Human Mobility Modelling

arXiv:2609.22117v1 Announce Type: new Abstract: Location representations provide mobility models with fundamental information about the spatial position, functional characteristics, and relationships

Learning Dynamic Neural Evidence Representations for Time-Adaptive Brain-Computer Interfaces

arXiv:2609.22088v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) decode neural activity into commands, yet most existing systems rely on fixed-window decoding that may result in redu

Lesion-Gated Hybrid Synthesis for Virtual Contrast-Enhanced Breast MRI: A MAMA-SYNTH Challenge Solution

arXiv:2609.22397v1 Announce Type: cross Abstract: Purpose: Contrast-enhanced breast MRI depends on intravenous gadolinium-based contrast agents, motivating methods that synthesise post-contrast appear

Leveraging Industrial Foundation Models at the Edge of Particle Physics Detectors via Distillation Learning and Hardware Co-design

arXiv:2609.23385v1 Announce Type: cross Abstract: Data acquisition (DAQ) systems at future particle physics experiments stand to benefit from the extremes of AI/ML development: large-scale foundation

LG-HCC: Local Geometry-Aware Hierarchical Context Compression for 3D Gaussian Splatting

arXiv:2603.28431v4 Announce Type: replace Abstract: Although 3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, its prohibitive storage overhead severely hinders practical deploym

LINGO: Latent Initialization and Gradient Optimization for Sparse-view X-ray Novel View Synthesis and CT Reconstruction with 3D Gaussian Splatting

arXiv:2609.22849v1 Announce Type: new Abstract: In novel view synthesis and Computed Tomography (CT) reconstruction with sparse-view X-ray imaging, insufficient angular coverage leads to structural am

Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

arXiv:2506.07044v5 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements, largely due to their lar

LiteTex-GS: Fast and Lightweight Texturing for Gaussian Splatting

arXiv:2609.23380v1 Announce Type: new Abstract: Gaussian Splatting has enabled real-time novel view synthesis, but its tightly coupled geometry and appearance representation often require a large numb

LLM-based Conversational AI Knowledge Assistant for MyBuddy Humanoid Robot

arXiv:2609.24742v1 Announce Type: new Abstract: Humanoid robots are increasingly being popular and developed for human-centered applications, yet their ability to provide intelligent conversations and

LLMs Anchor on Chief Complaint and Fail to Integrate Evidence in Sequential Clinical Triage

arXiv:2609.22904v1 Announce Type: new Abstract: Triage in the emergency department (ED) is a sequential decision process that unfolds turn by turn. Existing evaluations of large language models (LLMs)

LLMs as Linguistic Chameleons: Decoupling Semantics and Structure for Privacy-Preserving Communication

arXiv:2609.23193v1 Announce Type: cross Abstract: As Large Language Model (LLM) APIs become increasingly integrated into privacy-sensitive workflows, ensuring inference-time privacy without compromisi

Logits are All We Need to Adapt Closed Models

arXiv:2502.06806v5 Announce Type: replace-cross Abstract: Many commercial Large Language Models (LLMs) are often closed-source, limiting developers to prompt tuning for aligning content generation wit

Long-Tail Rebalancing for Non-Verbal Vocalization-Aware ASR: A Track~1 System for the NVVSpeech Challenge

arXiv:2609.23462v1 Announce Type: cross Abstract: Non-verbal vocalizations (NVVs) carry important paralinguistic information but are often omitted by conventional automatic speech recognition (ASR) sy

Low-Rank Frequency Convolution and Noise-Range Augmentation for Real-Time Pitch Estimation on Edge Devices

arXiv:2609.23340v1 Announce Type: cross Abstract: Pitch estimation on an edge device is constrained in three ways at once. The model must be small, it must stay accurate when the input is noisy, and o

LPINNs: First-Layer Gated Localization for Physics-Informed Neural Networks

arXiv:2609.22984v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use one shared representation over the computational domain, which can become difficult to optimize on long dom

MambaX: Image Super-Resolution with State Predictive Control

arXiv:2511.18028v2 Announce Type: replace Abstract: Image super-resolution (SR) is a critical technology for overcoming the inherent hardware limitations of sensors. However, existing approaches mainl

Matched-Input Estimates Differ in Sign Across Architectures: Auditing EEG Foundation Models on Motor Imagery

arXiv:2609.23924v1 Announce Type: new Abstract: Pretrained EEG foundation models are increasingly proposed as general-purpose encoders for brain-computer interfaces, yet recent benchmarks disagree abo

Math2Visual-X: A Modular Framework for Pedagogically Aligned Lower-Primary Math Visuals Generation

arXiv:2609.22647v1 Announce Type: new Abstract: Visual representations can help lower-primary learners understand Math Word Problems, but generating classroom-usable visuals remains difficult. Existin

Memory vs. Context? Influential Factors of Factual Recall in Language Models

arXiv:2609.24238v1 Announce Type: new Abstract: We reproduce and stress-test the work of Yu et al. (2023), who characterize how language models (LMs) arbitrate between memorized knowledge and contradi

Merge++: Universal Merge Refinement Through Data-Free Checkpoint Inversion

arXiv:2609.22886v1 Announce Type: new Abstract: Model merging consolidates fine-tuned experts into one multi-task model without retraining. All existing data-free methods approach this problem entirel

MGRD: Compact morphology-gated residual diffusion for variance-aware cross-domain neurite forecasting

arXiv:2609.23990v1 Announce Type: new Abstract: Tracking neurite morphology over time helps characterize structural changes during neuronal development and deterioration, but long-term time-lapse imag

MIGA:Shared-Geometry Gaussian Representation with Implicit Amplitude Modeling for Accelerated 3D Multi-Echo MRI

arXiv:2609.24468v1 Announce Type: new Abstract: Three-dimensional multi-echo MRI provides rich anatomical and quantitative information, but repeated volumetric encoding prolongs acquisition and motiva

Minimum Time Trajectories for a Car-Like Mobile Robot Moving with Rigid Wheels Under Non-Sliding Constraints

arXiv:2609.24832v1 Announce Type: new Abstract: This paper studies the minimum time trajectoriesvof a car-like mobile robot navigating in an obstacle free environment. The robot, with forward and back

MIRAGE: Full-Body Bystander Privacy for Smart Glasses with Consent-Based Restoration

arXiv:2609.24537v1 Announce Type: new Abstract: Video recording on smart glasses exposes more than faces. Continuous capture reveals full-body biometric signatures, including gait, posture, and silhou

MiTHras: Task-specific Hierarchical Semi-supervised Contrastive Masked Autoencoder for Mitotic Figure Analysis

arXiv:2609.24736v1 Announce Type: new Abstract: Mitotic figure (MF) analysis supports tumor grading and prognostic assessment, but automated models remain sensitive to differences in tissue type and i

Mitigating Entity Type Confusion in Cross-Domain NER via Multidimensional Quantification and Reasoning Enhancement

arXiv:2609.24357v1 Announce Type: new Abstract: Cross-domain Named Entity Recognition (CD-NER) aims to transfer the rich knowledge in the source domain to the target domain. Recent studies adopting de

Model-Agnostic Feature Selection via LOCO-Guided Adaptive Minipatch Sampling

arXiv:2609.24126v1 Announce Type: cross Abstract: Black-box machine learning models increasingly deliver strong predictions, but extracting useful information from them, such as a set of important fea

Modeling Clinical Workflow for SYNTAX Scoring from Coronary Angiography Videos

arXiv:2609.23553v1 Announce Type: new Abstract: The SYNTAX score is a clinically established tool for assessing anatomical lesion complexity in coronary artery disease and guiding subsequent treatment

Modelling daily activity patterns from mobile phone location data via deep representation learning

arXiv:2609.22121v1 Announce Type: new Abstract: Passively collected mobile phone location data provide large-scale, longitudinal observations of human mobility but do not directly reveal activity purp

Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring

arXiv:2609.22169v1 Announce Type: new Abstract: Employers are increasingly using large language models (LLMs) to automate their hiring process. This paper investigates the risk of monocultural biases,

Morpho-VITS: Variational Inference with Morphological Modeling for End-to-End Speech Synthesis of a Tonal Bantu Language

arXiv:2609.24310v1 Announce Type: cross Abstract: Text-to-speech models for Bantu tonal languages are challenged by a tonal system that is rooted in both the lexis (i.e., the inventory of words, stems

MR-SPITE: Accelerating Multi-Robot Conflict Scans via Hierarchical Swept-Volume Approximations

arXiv:2609.23928v1 Announce Type: new Abstract: Conflict scanning over synchronized robot paths requires detailed collision checking, potentially across every robot pair at every timestep, and may be