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COMPASS: Ordered Clustered Routing at 100K Scale

arXiv:2609.20352v1 Announce Type: new Abstract: Large-scale routing often requires visiting clusters of nodes in a prescribed order, giving rise to the Ordered Clustered Traveling Salesman Problem (OC

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

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DGX agent

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

model-releasesarxiv-cs-cl

18 Sept 2026

Compliance for Free: Learning Identifiable Impedance via Bilateral Teleoperation

arXiv:2609.19976v1 Announce Type: new Abstract: Vision-language-action models tell a robot where to move, but not how hard to push. Contact-rich tasks depend on that second quantity, compliance, yet n

Applications

Compositional Reasoning in Language Models under Reinforcement Learning Post-Training

arXiv:2609.19465v1 Announce Type: new Abstract: Compositional reasoning is critical for real-world problem solving: since training data is necessarily limited, models must generalize by composing lear

applicationsarxiv-cs-ai

Compressed Active Subspaces for Scalable Bayesian Inference

arXiv:2609.19539v1 Announce Type: cross Abstract: Active subspace methods provide a framework for quantifying predictive uncertainty in high-dimensional models by identifying and performing inference

Compression Hurts, Pooling Helps: Information Loss in Rayleigh-Scale Estimation from B-Mode Ultrasound

model-releasesarxiv-cs-cv

arXiv:2609.19525v1 Announce Type: cross Abstract: Clinical B-mode images are widely available as potential data sources for quantitative ultrasound (QUS) analysis for tissue characterization. However,

Conservation Buys Stability and Factoring Buys Counterfactuals in Physical World Models

arXiv:2609.19674v1 Announce Type: new Abstract: A learned simulator can reproduce its training conditions accurately yet fail in two distinct ways once those conditions change. Over long rollouts, sma

Constraint-Safe Graph-Context Scoring for Stable Point-Feature Labels Under Text-Width and Accessibility-Inspired Profiles

arXiv:2609.19848v1 Announce Type: new Abstract: Point-feature label placement on interactive maps must reconcile geometric validity, display yield, local placement utility, and stability across camera

Contagion on the Trading Floor: How Adversarial Signals Spread in Multi-Agent Trading Systems

arXiv:2609.19789v1 Announce Type: new Abstract: Multi-agent trading systems built on large language models (LLMs) are beginning to appear in quantitative finance, yet their robustness to adversarial i

Continual Enterprise World Model Discovery in Dynamic Systems

arXiv:2609.19551v1 Announce Type: new Abstract: In an enterprise system, updating one field can set another, create a record, or start an approval. These effects are produced by business rules that ar

agentsarxiv-cs-ai

CORAL-AUV: CFD Oriented Reinforcement Learning for Autonomous Underwater Vehicles

arXiv:2607.09557v2 Announce Type: replace Abstract: Fine grain control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Traditio

CoRe: Coherence and Relational Alignment for Multivariate Time Series Forecasting

arXiv:2609.19670v1 Announce Type: new Abstract: Direct forecasting has become a standard paradigm for multivariate time-series forecasting because it predicts the full future horizon in a single pass.

safetyarxiv-cs-lg

CoRef-GS: Cooperative Referring Gaussian Splatting for Multi-Agent Scene Understanding

model-releasesarxiv-cs-cv

arXiv:2609.20586v1 Announce Type: cross Abstract: Referring scene understanding for embodied robots requires grounding object- and relation-centric language queries from a designated viewpoint. While

CoRELoop: Parameter-Efficient Controlled Recurrent Refinement for Audio Deepfake Detection

arXiv:2609.19818v1 Announce Type: cross Abstract: Generalizing to unseen attacks remains challenging for audio deepfake detectors, and collecting training data covering all potential attacks is imprac

CoreSense: Traceable Failure Recall and Conflict-Aware Belief Gating for Auditable Robot Decisions

arXiv:2609.19512v1 Announce Type: cross Abstract: Robots can recall prior failures without knowing whether recalled evidence remains valid, conflicts with current observations, or is sufficient to gui

safetyarxiv-cs-ai

Correct Now, Insufficient Later: Auditing Update Sufficiency in Context Compression

arXiv:2609.20045v1 Announce Type: cross Abstract: A memory can answer a current query correctly while discarding distinctions required by a later update. We investigate this failure with a paired-hist

Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning

arXiv:2609.20461v1 Announce Type: cross Abstract: Studying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are

CounselReflect: Opportunities and Challenges for Designing Tools to Support Self-Reflection on Mental Health and Well-Being Conversations with AI

arXiv:2603.29429v2 Announce Type: replace Abstract: AI is increasingly used for mental health and well-being support, creating an urgent need for safer engagement, while design, evaluation, and govern

researcharxiv-cs-cl

Counterexamples and Sufficient Conditions: Comments on 'Optimally-Transported Generalized Method of Moments'

arXiv:2609.20260v1 Announce Type: cross Abstract: We comment on the optimally-transported generalized method of moments (OTGMM) estimator proposed by Schennach & Starck (2026a) and give counterexample

CovR: Coverage-Aware Hardware Verification via Reasoning-Guided Reinforcement Learning

arXiv:2609.19189v1 Announce Type: cross Abstract: Design verification remains one of the most resource-intensive stages of hardware development, often consuming up to 70% of the total design effort. W

agentsarxiv-cs-cl

Cross-Architecture Foundation-Model Distillation for Edge Flood Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.20441v1 Announce Type: new Abstract: Geospatial foundation models can provide strong flood-segmentation performance, but their size limits deployment on memory-constrained edge hardware. We

Cross-Modal Attention Acts as a Frequency Filter: Why Verbose Prompts Improve Robustness in Vision-Language Models

arXiv:2609.20139v1 Announce Type: cross Abstract: Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the question affects VLMs in two opposite ways. Verbose

Cross-Sectional Asset Retrieval via Future-Aligned Soft Contrastive Learning

arXiv:2602.10711v2 Announce Type: replace-cross Abstract: Asset retrieval (finding similar assets in a financial universe) is central to quantitative investment decision-making. Existing approaches de

CrystalMO-TuRBO: Multi-Objective Trust-Region Bayesian Optimization for High-precision Joint Crystal Structure Refinement

arXiv:2609.20592v1 Announce Type: new Abstract: Crystal structure refinement is a fundamental inverse problem in materials characterization, where structural parameters are optimized to reproduce expe

Custom PX4 firmware for autonomous hybrid aerial-marine missions

arXiv:2609.20691v1 Announce Type: new Abstract: Mapping and monitoring aquatic environments can benefit from hybrid aerial-amphibious drones able to combine flight and water-surface navigation within

Applications

Customizable and Jointly Optimized Route Planning: A Deep Architecture Enabling Differentiable Shortest-Path Search

arXiv:2609.19996v1 Announce Type: new Abstract: With the widespread use of online navigation and ride-hailing services, achieving optimal route planning for diverse user preferences has recently attra

applicationsarxiv-cs-ai

D-Quant: Driftable Entropy Coding for KV Cache Quantization

arXiv:2609.19880v1 Announce Type: new Abstract: The KV cache has become a major bottleneck in deploying LLMs, as its memory footprint grows linearly with sequence length and batch size, imposing subst

researcharxiv-cs-cl

DART: Distillation-Aware Reparameterization for Training-Free LoRA Reuse in Few-Step Video Diffusion Models

arXiv:2609.20051v1 Announce Type: new Abstract: Step distillation reduces the cost of video generation, but reusing a LoRA trained for a longer trajectory can alter its functional effect or degrade ta

DataCanvas-EDU: An Agentic Framework for Instructor-Guided Synthetic Data Generation in Business Analytics Education

arXiv:2609.19617v1 Announce Type: cross Abstract: Business analytics education requires diverse datasets to support different learning objectives, student backgrounds, and analytical tasks. Real-world

agentsarxiv-cs-ai

Decoupling Physical Speed from Path Parameterization in Singularity-Free Guiding Vector Fields

arXiv:2609.19726v1 Announce Type: new Abstract: The existing singularity-free guiding vector field (SF-GVF) with an additional virtual coordinate can eliminate singular points (i.e., points where the

researcharxiv-cs-ro

Deep Learning-Based Classification of Cognitive and Resting States Using Electroencephalography Signals

arXiv:2609.20467v1 Announce Type: cross Abstract: The categorization of cognitive and resting states derived from electroencephalography (EEG) signals is crucial for comprehending fluctuations in brai

Deep Learning Detection of Beyond-General-Relativity Deviations in Gravitational-Wave Signals: A Detection-Threshold Study with Real LIGO Noise

arXiv:2609.19416v1 Announce Type: cross Abstract: We study machine-learning detection of controlled beyond-General-Relativity (beyond-GR) deviations in gravitational-wave signals, using both synthetic

Deep Noir: Autonomous Steering Discovery via Architectural Chronometry in Transformer Models

arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a f

agentsarxiv-cs-ai

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

model-releasesarxiv-cs-cl

arXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost

DeliveryGym: An RL Environment for Long-Horizon Embodied Agent Planning with Adaptive Curriculum

arXiv:2609.19801v1 Announce Type: new Abstract: Executable environments enable LLM agents to learn from the consequences of their actions. For embodied agents, those consequences extend beyond whether

safetyarxiv-cs-lg

Delphi Scanner: efficient and interpretable static malware detection via API sequence modeling

arXiv:2609.19900v1 Announce Type: cross Abstract: Static malware detection for Windows Portable Executable files demands a careful balance between detection effectiveness, computational efficiency, an

DeltaSelect: Affordable A/B Testing for Coding Agents

arXiv:2609.19607v1 Announce Type: cross Abstract: Coding-agent benchmarks are built for broad and comprehensive comparisons, not frequent development decisions. Individual runs vary, full suites are e

Demystifying Linear Operator Learning for Control Systems

arXiv:2609.19428v1 Announce Type: cross Abstract: This paper proposes a structured approach to learning linear operators for control systems from data. We address both structural and learning-theoreti

Design and Experimental Validation of a 3D Printed Torsional Series Elastic Actuator for Safe Human Robot Interaction

arXiv:2609.19367v1 Announce Type: new Abstract: Ensuring intrinsic safety in physical human robot interaction (pHRI) is a critical requirement for social and service robots. While Series Elastic Actua

Design of the IBM Granite 5.0 TurboCTC ASR Model

model-releasesarxiv-cs-cl

arXiv:2609.20104v1 Announce Type: new Abstract: We describe the architecture, training methodology and inference speedups of Granite 5.0 Turbo CTC, a 470 million parameter encoder-only model with an e

Tutorials

Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants

arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling. However, it remains unclear how to prevent deski

tutorialsarxiv-cs-ai

Applications

Detecting Deceptive Recruitment: A Signal-theoretic Machine Learning Framework for Early Identification of Labour Exploitation

arXiv:2609.20336v1 Announce Type: cross Abstract: Deceptive online job advertisements have emerged as a primary pathway into forced labour, yet systematic detection methods remain underdeveloped due t

applicationsarxiv-cs-lg

Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication

arXiv:2609.19531v1 Announce Type: cross Abstract: We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for mul

DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation

arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots

safetyarxiv-cs-cv

Diagnose, Recover, Certify: Task Readiness under Hidden Dynamics Changes

arXiv:2609.20304v1 Announce Type: new Abstract: A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the pol

safetyarxiv-cs-ai

Dictionary-Constrained Grapheme-to-Phoneme for Unsegmented Languages from LLM-Annotated Data

model-releasesarxiv-cs-cl

arXiv:2609.19805v1 Announce Type: new Abstract: Grapheme-to-phoneme (G2P) conversion turns raw text into its phonemic form and is an essential part of both text-to-speech (TTS) and automatic speech re

Digital Twins for Opinion Dynamics: A Generative LLM Framework for Social Networks

arXiv:2609.19913v1 Announce Type: new Abstract: The study of opinion dynamics in social networks is one of the key challenges in computational social science with direct relevance to understanding pol

Hardware

DirtyMoCap: Robust Motion Capture from Unconstrained Markers

arXiv:2609.19927v1 Announce Type: new Abstract: Optical motion capture delivers high-fidelity human motion, but its reliance on strict marker layouts and clean trajectories severely limits its real-wo

hardwarearxiv-cs-cv