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Compositional Shift Algebra: Extrapolating Mixed Robot Shifts Without Mixed Finetuning

model-releasesarxiv-cs-cv

arXiv:2609.13651v1 Announce Type: cross Abstract: Robot deployments rarely change one mechanism at a time: cameras, action interfaces, and physical dynamics often shift together. Prior adaptation reci

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Compositional SVG Generation via VLM-Driven Hierarchical Semantic Parsing

DGX agent

arXiv:2609.14657v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) excel at visual reasoning, generating structured, editable Scalable Vector Graphics (SVG) remains a fundamental ch

model-releasesarxiv-cs-ai

15 Sept 2026

Local Ai

Concept-Grounded Reasoning with Prompt-Driven Localization for Interpretable Structured Report Generation

arXiv:2609.15334v1 Announce Type: cross Abstract: Medical imaging modalities such as ultrasound and X-ray are widely used in clinical practice, where diagnosis follows a structured, evidence-driven wo

local-aiarxiv-cs-ai

Conditional Quantum Flow Matching for Data-Scarce Physiological Signal Augmentation

model-releasesarxiv-cs-lg

arXiv:2609.14019v1 Announce Type: cross Abstract: Generative augmentation is a standard remedy for label scarcity in physiological signal classification, but existing quantum generative models start f

ConeGaussian: Anti-Aliased Gaussian Ray-Tracing for Generic Central Cameras

arXiv:2609.13397v1 Announce Type: new Abstract: In rendering, a camera is a sampling operator that maps each finite pixel to a bundle of rays. Different camera models change the geometry of this bundl

researcharxiv-cs-cv

Confident Rankings with Fewer Items: Adaptive LLM Evaluation with Continuous Scores

arXiv:2601.13885v2 Announce Type: replace-cross Abstract: Computerized Adaptive Testing (CAT) has proven effective for efficient LLM evaluation on multiple-choice benchmarks, but modern LLM evaluation

Local Ai

Conflict-Predictive Variable Horizons in Multi-Drone Distributed Model Predictive Control

arXiv:2609.13270v1 Announce Type: cross Abstract: In distributed model predictive control for multi-drone collision avoidance, a fixed prediction horizon forces a compromise: a short horizon is inexpe

local-aiarxiv-cs-ai

Conformal Individual Treatment Effect Estimation under Networked Interference

arXiv:2609.15254v1 Announce Type: cross Abstract: Conformal counterfactual prediction constructs prediction sets with finite-sample coverage guarantees for counterfactual outcomes and individual treat

Confuse the Model, Control the Flow: Understanding and Mitigating Privacy Leakage from LLM Agents with Information Flow Control

arXiv:2609.14003v1 Announce Type: cross Abstract: Personal AI agents built on large language models (LLMs) are increasingly given access to a user's private data and communications in order to provide

agentsarxiv-cs-ai

Consistency of augmentation graph and network approximability in contrastive learning

arXiv:2502.04312v3 Announce Type: replace Abstract: Contrastive learning leverages data augmentation to develop feature representation without relying on large labeled datasets. However, despite its e

Constraint-Grounded Reinforcement Learning for Variable Impedance Control in Contact-Rich Robotic Insertion

arXiv:2609.13516v1 Announce Type: new Abstract: In robotic insertion under uncertain contact, the axial force limit and the appropriate controller gain vary across tasks. As a result, a single fixed g

safetyarxiv-cs-ro

Applications

Context-Aware Mutual Learning for Blind Image Inpainting and Beyond

arXiv:2609.14439v1 Announce Type: new Abstract: Blind image inpainting, aiming to recover contaminated images in the case of unknown masks, is a challenging task. Motivated by the perspective of human

applicationsarxiv-cs-cv

Context-Dependent Affordance Reports in Vision-Language Models

arXiv:2603.04419v3 Announce Type: replace-cross Abstract: Vision-language models produce different object and use descriptions under different persona prompts, but low overlap alone does not identify

Continuous Manifold-Decomposed Impedance Retargeting for Contact-Rich Imitation Learning

arXiv:2609.15716v1 Announce Type: new Abstract: CMDIR extends Manifold-Decomposed Impedance Retargeting (MDIR) to transform fixed-impedance demonstrations into continuous variable-impedance controller

researcharxiv-cs-ro

Contour-Guided Spectral Routing for Robust Real-Time Pedestrian Detection

arXiv:2609.14383v1 Announce Type: new Abstract: Real-time pedestrian detection in driving scenes is constrained by three coupled failure modes: tiny targets lose discriminative evidence, occlusion wea

safetyarxiv-cs-cv

Controllable Dysarthric Speech Synthesis with Patient-Specific Conditioning for Speaker-Diverse ASR Augmentation

arXiv:2602.08696v3 Announce Type: replace-cross Abstract: Dysarthric speech recognition is limited by high speaker variability and scarce labeled data. Existing synthesis methods often couple speaker

researcharxiv-cs-cl

Converge Then Diversify: Decoupling Convergence and Diversity in Multi-Objective Bayesian Optimisation

arXiv:2609.13396v1 Announce Type: new Abstract: Multi-objective Bayesian optimisation (MOBO) is a sample-efficient approach for optimising expensive black-box functions with multiple objectives. In MO

Convergence Analysis of Sequential Federated Learning on Heterogeneous Data

arXiv:2311.03154v3 Announce Type: replace Abstract: There are two categories of methods in Federated Learning (FL) for joint training across multiple clients: (i) parallel FL (PFL), where clients trai

Convergence, design and training of continuous-time dropout as a random batch method

arXiv:2510.13134v2 Announce Type: replace Abstract: We study continuous-time dropout in controlled differential equations. We introduce a random-batch approximation of additive vector fields. On each

Convergence rates for generative drifting flows: fixed-scale obstructions and multihead acceleration

arXiv:2609.15193v1 Announce Type: new Abstract: Drifting models offer a promising route to faster generative AI: they perform gradual transport during training, while generating new samples in a singl

Convergent Emergence of In-Context Learning Across Modalities

arXiv:2609.14011v1 Announce Type: new Abstract: Few-shot in-context learning (ICL), the capacity of a model to infer abstract patterns from input-output examples provided in its prompt and apply them

Converting Sequenced Fuzzy Cognitive Maps to Causal Virtual Worlds with Large Video Generators

arXiv:2609.14985v1 Announce Type: new Abstract: We show how users can create and manipulate causal virtual worlds with large-language-model (LLM) and large-video-model agents. The approach uses feedba

Corpus Characterization and Inverse Constitutional Fine-Tuning for Style-Aware Radiology Reports

arXiv:2609.14226v1 Announce Type: new Abstract: Automated radiology report generation has advanced rapidly in diagnostic accuracy, yet generated reports frequently diverge from the stylistic conventio

safetyarxiv-cs-cl

Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection

arXiv:2609.15989v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is a safety strategy where the reasoning of a large language model 'actor' is inspected by a 'monitor' (often another

Cost Characterization of Vertically Partitioned Federated Knowledge Graphs

arXiv:2609.13664v1 Announce Type: new Abstract: Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming

agentsarxiv-cs-ai

Covariance-Regulated Recursive Koopman Learning for Nonlinear Systems with Uncertain Time-Varying Dynamics

model-releasesarxiv-cs-ro

arXiv:2606.15317v2 Announce Type: replace Abstract: Offline models for autonomous robots often fail under time-varying dynamics outside their training distribution. While Koopman operator theory offer

CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection

arXiv:2609.13842v1 Announce Type: cross Abstract: Recent advances in speech synthesis and voice conversion have made deepfake speech increasingly realistic, making generalization to unseen spoofing at

CREPES-X: Hierarchical Bearing-Distance-Inertial Direct Cooperative Relative Pose Estimation System

arXiv:2512.24688v2 Announce Type: replace Abstract: Relative localization is essential for cooperation in autonomous multi-robot systems. Existing approaches either rely on shared environmental featur

agentsarxiv-cs-ro

Criticality in Dissimilar Decomposition and Undersampling of Random Datasets with Anomalies

arXiv:2609.13201v1 Announce Type: new Abstract: Training datasets for upcoming LLMs would include a significant amount of AI text/image data generated from current LLMs. In such a scenario, it is impo

Applications

CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

arXiv:2609.13942v1 Announce Type: cross Abstract: The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs)

applicationsarxiv-cs-ai

Cross-Block Conditioning in Deep Boltzmann Machines for Statistical Data Fusion

arXiv:2609.14934v1 Announce Type: cross Abstract: Statistical data fusion combines two panels that share a block of covariates but observe disjoint outcome blocks, and in its traditional form no row o

CrossDistill: Balancing Quality and Diversity via Trajectory-Level Hybrid Few-Step Distillation

arXiv:2609.14725v1 Announce Type: new Abstract: Few-step distillation accelerates diffusion models but must balance diversity and fidelity: trajectory-based distillation preserves mode coverage, while

safetyarxiv-cs-cv

Crypto Accounting Bench: Evaluating Frontier and Open-Weight Models on Crypto-Asset Accounting Tasks

arXiv:2609.14811v1 Announce Type: new Abstract: We introduce Crypto Accounting Bench (CAB), a benchmark for assessing whether frontier and open-weight language models can reconstruct the complete jour

Curvature-Independent Regret Bounds for Distributed Online Optimization on Hadamard Manifolds

arXiv:2609.13646v1 Announce Type: new Abstract: This work addresses decentralized online Riemannian optimization on Hadamard manifolds. Prior work under geodesic convexity (g-convexity) may require cu

CVSS-X: A Multilingual Speech-to-Speech Translation Corpus for 28 Languages

arXiv:2609.13413v1 Announce Type: new Abstract: We introduce CVSS-X, a large-scale synthetic speech-to-speech translation corpus that extends CVSS by reversing the translation direction. While CVSS tr

researcharxiv-cs-cl

CWM: Controllable White-Box Meta-Prompting for Adaptive Retrieval-Augmented Generation and Reasoning Ability

arXiv:2609.15234v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have gained significant attention due to their strong language understanding and generation capabilities, demonst

CyclOT: Learning Quadratic Optimal Transport Maps via Synchronized Forward-Backward Interpolants

arXiv:2609.13892v1 Announce Type: cross Abstract: We study the recovery of forward and reverse quadratic optimal-transport maps from unpaired samples in high dimensions. We introduce a bidirectional n

CyFM: Cylindrical Optimal Transport for Few-Step Complex-Valued Flow Matching

arXiv:2609.14171v1 Announce Type: new Abstract: Complex-valued signals, such as Magnetic Resonance Imaging (MRI) and audio spectrograms, are almost always modelled as flat two-channel Euclidean data.

DA-DLM: Explicitly Modeling Token Dependencies in Diffusion Language Models

arXiv:2609.15070v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) generate text by iteratively denoising a masked sequence, independently predicting multiple tokens at each step. This c

researcharxiv-cs-cl

DARE: Dialectical Agentic Reasoning for Structured Knowledge Fact Checking

arXiv:2609.13808v1 Announce Type: new Abstract: Structured knowledge fact checking aims to determine the truthfulness of natural language claims by reasoning over structured evidence. Recent program-g

agentsarxiv-cs-cl

Data Attribution at Scale via Influence Matrix Estimation

arXiv:2609.15044v1 Announce Type: cross Abstract: Data attribution seeks to quantify how individual training examples shape a model's predictions and underpins problems including data valuation, machi

Data-driven Prediction of Satellite-observed Avalanche Activity from Snowpack Simulations

arXiv:2609.15485v1 Announce Type: new Abstract: Avalanche forecasting requires knowledge of snowpack conditions and recent avalanche activity, but field observations are sparse across large mountain r

Data-Efficient Agentic Graph Domain Adaptation via Reliability-Aware Prototype Learning

arXiv:2609.14045v1 Announce Type: new Abstract: Agentic learning systems are often required to adapt after deployment by observing new data and reusing prior knowledge under limited supervision or fee

agentsarxiv-cs-lg

Data Efficient Any Transformer-to-Mamba Distillation via Attention Bridge

arXiv:2510.19266v3 Announce Type: replace Abstract: State-space models (SSMs) have emerged as promising alternatives to Transformers for sequence modeling. However, training competitive SSMs from scra

safetyarxiv-cs-lg

Data-free On-policy Distillation

arXiv:2609.14193v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a standard component of frontier post-training pipelines, yet how much its training data actually contributes

safetyarxiv-cs-ai

Data Security in Large Language Models: Risks, Defense, and Directions

arXiv:2508.02312v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine t

agentsarxiv-cs-ai

Applications

Data storytelling meets interpretable machine learning: Decoding AI decisions for non-experts without revealing sensitive data and model details

arXiv:2609.15722v1 Announce Type: new Abstract: AI-driven automated decision-making requires both predictive performance and interpretability. Recent advances in interpretable machine learning (IML) p

applicationsarxiv-cs-ai

Decentralized Multi-Robot Task Allocation Under Degraded Communication: A Benchmark of Performance, Reliability, and Computation

model-releasesarxiv-cs-ro

arXiv:2609.13711v1 Announce Type: new Abstract: Selecting a decentralized Multi-Robot Task Allocation (MRTA) method for embedded deployment on autonomous platforms requires considering more than route