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Context-aware Skin Cancer Epithelial Cell Classification with Scalable Graph Transformers

arXiv:2602.15783v2 Announce Type: replace Abstract: Whole-slide images (WSIs) from cancer patients contain rich information that can be used for medical diagnosis or to follow treatment progress. To a

researcharxiv-cs-cv

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Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

DGX agent

arXiv:2609.29194v1 Announce Type: cross Abstract: Mobile robots require robust, real-time fault detection capable of continuous adaptation on constrained edge hardware. While deep time-series models e

model-releasesarxiv-cs-lg

25 Sept 2026

Control the Harness, Control the Cost: Routing and Governing AI Coding Agents in the Enterprise

arXiv:2609.28919v1 Announce Type: new Abstract: Harnesses, the products that run AI coding agents, are multiplying, and enterprises are rolling them out to their employees: what started as pilots with

Controlling Backchannels in Streamable Full-duplex Models

arXiv:2609.29418v1 Announce Type: new Abstract: Backchannels, brief acknowledgements like 'uh-huh' produced while the other party may still be talking, are central to natural conversation, but full-du

researcharxiv-cs-cl

Conversational DNA: A Visual Language and Interactive Atlas of Human and AI Dialogue

arXiv:2508.07520v2 Announce Type: replace-cross Abstract: What makes a conversation hold together when its participants speak across one another? Topic maps offer one view, but they leave the relation

Coordinate-Independent Robot Model Identification

arXiv:2603.14656v2 Announce Type: replace Abstract: Robot model identification is commonly performed by least-squares regression on inverse dynamics, but existing formulations measure residuals direct

safetyarxiv-cs-ro

Tutorials

CORDIAL: Calibrating Ordinal LLM Outputs from Few Labels

arXiv:2609.29807v1 Announce Type: new Abstract: A large language model (LLM) can turn a text into a distribution over an ordered scale, but that distribution is a noisy measurement: saturated, compres

tutorialsarxiv-cs-cl

Cost-Sensitive Online Window Size Selection for Portfolio Management

arXiv:2609.29887v1 Announce Type: cross Abstract: This paper investigates cost-sensitive online window size selection for portfolio management under changing market conditions. Specifically, we propos

researcharxiv-cs-lg

CoSWA-YOLOv12: Scale-Invariant Tiny Object Detection and Segmentation of Malaria Parasites

arXiv:2609.29527v1 Announce Type: cross Abstract: Automated microscopy could widen access to malaria diagnosis in low-resource settings, but the deadliest species, P. falciparum, presents in its early

local-aiarxiv-cs-ai

CounterRoute: Self-Routed Reasoning via Hierarchical Counterfactual Credit Assignment

arXiv:2609.29109v1 Announce Type: new Abstract: Reasoning-capable language models often produce long chains of thought when direct answers suffice, wasting inference compute. Many dual-mode models lea

Coupled State-Space Modelling, Control, and Policy Distillation for Hybrid Rigid-Pneumatic Manipulators

arXiv:2609.29424v1 Announce Type: new Abstract: Hybrid manipulators combine motorized rigid joints with pressure-actuated origami segments. Published arms of this kind are controlled with decoupled pe

safetyarxiv-cs-ro

CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer Registrars

arXiv:2609.29075v1 Announce Type: new Abstract: Cancer registrars, including Oncology Data Specialists (ODSs), must interpret complex and frequently updated coding and staging standards. We developed

Cross-Country Code-Mixing for Generative Recommendation

arXiv:2609.28972v1 Announce Type: cross Abstract: Cross-country recommendation on modern e-commerce platforms is typically deployed with disjoint user and item ID spaces across markets, removing the s

Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

arXiv:2609.29556v1 Announce Type: new Abstract: Multimodal emotion recognition is a key research area in affective computing, with applications in sentiment analysis, intelligent customer service, and

local-aiarxiv-cs-ai

Cross-Task Generalization in Handwriting-Based Alzheimer's Screening via Vision Language Adaptation

arXiv:2511.05841v2 Announce Type: replace-cross Abstract: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder for which early detection is critical. Handwriting, which can be disrupted

local-aiarxiv-cs-ai

CrossSafe: Towards Cross-Embodiment Latent Safety Filters

arXiv:2609.28984v1 Announce Type: cross Abstract: Cross-embodiment learning has shown that a single model, such as a vision-language-action (VLA) model, can learn state representations and manipulatio

CrossScale-GLIO: Topology-Preserving Vision-Language Alignment of MRI and Whole-Slide Histopathology for Diffuse Glioma

arXiv:2609.28524v1 Announce Type: cross Abstract: Magnetic resonance imaging and histopathology observe the same glioma at radically different scales. We present CrossScale-GLIO, a visual multimodal f

Cultural Divergence Preservation: Diagnosing Flattening and Caricature in LLM-Simulated Survey Populations

arXiv:2609.29928v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents to estimate population response distributions. In cross-cultural su

DA-GRD: Decision-Aware Grasp-Relevant Disambiguation for tactile recovery under perception-to-execution mismatches

arXiv:2609.29065v1 Announce Type: new Abstract: Grasping is a fundamental robotic capability that bridges perception and physical task execution. This paper studies grasp pose recovery under a percept

applicationsarxiv-cs-ro

DAWN: Noise-Robust Quadruped Parkour via Depth-Denoising World Models

arXiv:2609.29092v1 Announce Type: cross Abstract: Vision-based legged locomotion methods assume clean depth at training time and rely on hand-tuned post-processing filters at deployment. However, filt

DCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution

arXiv:2401.08875v3 Announce Type: replace-cross Abstract: Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While re

Decision Hijacking: Prompt Injection Attacks on Jev's Typed Probabilistic Decisions

arXiv:2609.28613v1 Announce Type: cross Abstract: Most studies of prompt injection focus on generative agents, leaving their effects on models with schema-defined outputs unclear. We examine these eff

Decoding Imagined Speech: A Strictly Subject-Independent Approach Using EEG

arXiv:2609.29820v1 Announce Type: new Abstract: Imagined speech decoding from electroencephalography (EEG) has gained increasing attention as a potential communication pathway for individuals with sev

Decoupled Early Exits for Task-Dependent Compute Allocation in Flow-Matching VLAs

arXiv:2609.29382v1 Announce Type: cross Abstract: Flow-matching Vision-Language-Action (VLA) models have emerged as a potential solution for generalist robot control, designed by combining a pretraine

safetyarxiv-cs-lg

Decoupled Learning and Selection in Slate Recommendation for Privacy and Stability Under Noisy Scores

arXiv:2609.29453v1 Announce Type: new Abstract: We formalize slate recommendation as a randomized score learner followed by deterministic selection. First, an appropriately scoped differential-privacy

researcharxiv-cs-lg

Decoupling Knowledge and Privacy: Post-Task Self-Distillation Replay for LLM Continual Learning

arXiv:2609.29711v1 Announce Type: cross Abstract: Privacy-preserving continual learning (PPCL) must reduce the reproduction of sensitive content while retaining useful knowledge across sequential task

Deep learning of longitudinal visual fields predicts glaucoma progression rate and identifies fast progressors

arXiv:2609.29256v1 Announce Type: cross Abstract: Glaucoma is the leading cause of irreversible blindness, and timely identification of fast progressors is essential to prevent disability. Current pra

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data

arXiv:2405.18929v3 Announce Type: replace-cross Abstract: Semi-supervised anomaly detection, which aims to improve the anomaly detection performance by using a small amount of labeled anomaly data in

DEEPO: Dual-Entropy Enhanced Policy Optimization for Hallucination in MLLMs

arXiv:2609.28570v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used to sharpen reasoning in multimodal large language models (MLLMs), yet its effect on hallucination is uneven.

Delay-of-Gratification as a Multi-Agent Survival Micro-benchmark for Long-Horizon LLMs: Social Exposure, Personas, and Tool Use Budgets

arXiv:2609.29509v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as multi-turn agents that must sustain goals, use tools, and adapt to other agents over extended

DeltaWAM: Delta World Action Models for Bimanual Manipulation

arXiv:2609.28811v1 Announce Type: new Abstract: World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and a

applicationsarxiv-cs-cv

Agents

Dense Coverage, Sparse Refinement: Byte-Constrained Cooperative Perception

arXiv:2609.29456v1 Announce Type: new Abstract: Collaborative perception improves autonomous perception by sharing intermediate Bird's-Eye-View (BEV) features across connected agents, but dense featur

agentsarxiv-cs-cv

Dense-Joint-Based Obstacle-Aided Locomotion with a Joint-Repositionable Snake Robot

arXiv:2609.29261v1 Announce Type: new Abstract: Obstacle-aided locomotion is a fundamental capability for snake robots to traverse complex environments. However, conventional rigid-link snake robots o

researcharxiv-cs-ro

Design and Evaluation of LLM Chaining-Based Task Planning for General Purpose Service Robots

arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to interpret diverse natural language commands an

Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning

arXiv:2603.17174v2 Announce Type: replace-cross Abstract: Code generation large language models (LLMs) are increasingly integrated into modern software development workflows. Recent work has shown tha

applicationsarxiv-cs-ai

Detecting Glaucoma Across Multi-ethnic Myopic and Non-Myopic Populations Using an Uncertainty-Aware Vision Transformer: A Multicentre Model Development and Validation Study

arXiv:2609.29433v1 Announce Type: cross Abstract: Background: Artificial intelligence (AI)-based glaucoma detection from colour fundus photographs (CFP) offers scalable screening, but performance may

Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attack

arXiv:2506.19886v3 Announce Type: replace-cross Abstract: Semantic communication enhances transmission efficiency by conveying semantic information rather than raw input symbol sequences. Task-oriente

researcharxiv-cs-lg

Tutorials

Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs

arXiv:2609.29466v1 Announce Type: cross Abstract: Approximate message passing on factor graphs underlies two dominant families of probabilistic inference algorithms: expectation propagation (EP) and v

tutorialsarxiv-cs-ai

Direction-Scale Decomposition in Action Representation: Rethinking What to Tokenize for Vision-Language-Action Models

arXiv:2609.28865v1 Announce Type: new Abstract: Action representation plays a central role in discrete-token vision-language-action (VLA) learning but remains underexamined. Under conventional pose-in

applicationsarxiv-cs-cv

DiscoPhon: Benchmarking the Unsupervised Discovery of Phoneme Inventories With Discrete Speech Units

model-releasesarxiv-cs-cl

arXiv:2603.18612v2 Announce Type: replace Abstract: We introduce DiscoPhon, a multilingual benchmark for evaluating unsupervised phoneme discovery from discrete speech units. DiscoPhon covers 6 dev an

Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

model-releasesarxiv-cs-lg

arXiv:2609.29974v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects from observational data is difficult because the most appropriate inductive bias varies with overlap, treatme

Do Audio Language Models Hear and Read Distinctive Features Alike?

arXiv:2609.30167v1 Announce Type: new Abstract: Audio language models pass speech and text through a single decoder. We ask whether that decoder represents a distinctive feature in the same direction

researcharxiv-cs-cl

Do World Models Make Better Robots? A Survey of Evaluation Benchmarks for Predictive Embodied Intelligence

arXiv:2609.29669v1 Announce Type: cross Abstract: Robot learning now advances along two tracks that rarely meet. On one side, direct Vision-Language-Action (VLA) policies map observations to actions a

Agents

DocuTeam: Mixed-Initiative Multi-Agent Discussions around Evolving Documents

arXiv:2609.29309v1 Announce Type: cross Abstract: In open-ended problem solving, collaborators often rely on discussion to surface concerns, challenge perspectives, and refine shared work as it evolve

agentsarxiv-cs-ai

Does a model's stated reason for rejecting a candidate do any work?

arXiv:2609.30151v1 Announce Type: cross Abstract: Asked to choose between candidates and explain the choice, a language model often rejects a rival by naming a fact its profile lacks: no director, no

Does DCGAN-Based Synthetic Augmentation Improve Brain Tumor MRI Classification? An Empirical Study

arXiv:2609.28508v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) are increasingly used to augment medical imaging datasets, but synthetic images do not necessarily provide down

researcharxiv-cs-cv

Does per-frame early exit pay? A compute-matched study of dynamic depth for on-device speech enhancement

arXiv:2609.29867v1 Announce Type: cross Abstract: Deep learning-based speech enhancement is increasingly deployed on-device in hearing aids, headsets, and earbuds. Most of these devices, however, can

local-aiarxiv-cs-lg

Domain Recentering and Confidence-Weighted Prior Calibration for Vision-Language Models

arXiv:2609.29358v1 Announce Type: cross Abstract: Vision-language models such as CLIP achieve strong zero-shot classification, yet under distribution shift, visual embeddings drift from fixed text emb