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CHOREO: Every Humanoid Skill as a Trajectory

arXiv:2609.22274v1 Announce Type: new Abstract: Recent advances in humanoid robotics have produced diverse skills through reinforcement learning, motion imitation, and generative modeling. Yet these c

researcharxiv-cs-ro

Chronologic: Measuring Language Models' Ability to Represent the Past

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DGX agent

arXiv:2609.23178v1 Announce Type: new Abstract: Language models are appealing tools for research on the past. But to trust the evidence a model provides, researchers need to know whether its responses

model-releasesarxiv-cs-cl

22 Sept 2026

CIG-MAE: Cross-Modal Information-Guided Masked Autoencoder for Self-Supervised WiFi Sensing

arXiv:2512.04723v2 Announce Type: cross Abstract: Human Action Recognition using WiFi Channel State Information (CSI) has emerged as an attractive alternative to vision-based methods due to its ubiqui

Circuit-Diff: Factual Edit-based Intervention Method for Localizing Knowledge in Attribution Graphs

arXiv:2609.23892v1 Announce Type: new Abstract: Mechanistic interpretability defines features as the fundamental units of a neural network and circuits as the weighted subgraphs that carry out its com

Circuit Hypernetworks for Quantum-Augmented Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2609.24657v1 Announce Type: cross Abstract: Language models can be adapted by changing the computations applied to individual tokens. Quantum circuits offer one such approach, but evaluating wid

Classification with Abstention Under Class-Conditional Error Constraints

arXiv:2609.22632v1 Announce Type: new Abstract: We study binary classification with abstention under separate class-conditional error constraints, with the objective of minimizing abstention while kee

Classifier-Free Guidance in Flow Matching: Non-Autonomous Potentials, Overshoot, and Posterior-Mean Control

arXiv:2609.24287v1 Announce Type: new Abstract: Classifier-free guidance (CFG) improves conditional generation in Flow Matching, but strong guidance can distort the generated distribution and reduce d

safetyarxiv-cs-cv

CleanScore: Black-Box Benchmark Audits with Negative Controls and Sensitivity Bounds

arXiv:2609.22183v1 Announce Type: new Abstract: Public benchmark scores may reflect skill, prior exposure to the questions, or both, and for most models the training data are unknown. We present Clean

CLEAR: Complex Learned Explicit Analytical Regularization for Ultra-Accelerated 4D Flow CMR Reconstruction

arXiv:2609.22950v1 Announce Type: new Abstract: While compressed-sensing regularizers enable interpretable reconstruction of 4D Flow CMR through transparent variational objectives, their hand-crafted

Climate Variability Modulates the Impact of Price Spikes on Food Insecurity

arXiv:2609.24394v1 Announce Type: new Abstract: Climate variability influences whether a market disruption escalates into a food crisis, yet broad climate patterns like El Nino, tracked months before

Clinical Domain Classification from Medical Transcriptions

arXiv:2609.22734v1 Announce Type: new Abstract: Clinical domain classification plays an important role in organizing and analyzing large volumes of unstructured medical text. However, medical transcri

researcharxiv-cs-cl

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

arXiv:2504.14280v2 Announce Type: replace Abstract: As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for improving model robustness across diverse

safetyarxiv-cs-cv

CLOOPD: Closing the Learner Loop in On-Policy Distillation

arXiv:2609.24141v1 Announce Type: new Abstract: On-policy distillation (OPD) pays twice for each fresh batch: the student generates trajectories and a stronger teacher scores them. Existing methods im

safetyarxiv-cs-lg

Closed-Circuit Television Data as an Emergent Data Source for Urban Rail Platform Crowding Estimation

arXiv:2508.03749v2 Announce Type: replace Abstract: Accurately estimating urban rail platform occupancy can support more informed operational decision-making by transit agencies, particularly during p

Closing the Speech-Text Gap with Limited Audio for Effective Domain Adaptation in LLM-Based ASR

arXiv:2604.06487v2 Announce Type: replace Abstract: Conventional end-to-end automatic speech recognition (ASR) systems rely on paired speech-text data for domain adaptation. Recent LLM-based ASR archi

safetyarxiv-cs-cl

Tutorials

Clustering-Based Collective Anomaly Detection in IoT Systems: A Graph Neural Network Approach

arXiv:2609.22166v1 Announce Type: new Abstract: The rapid advancement of Internet of Things (IoT) technology has led to the widespread deployment of smart, interconnected devices across a range of dom

tutorialsarxiv-cs-lg

Local Ai

CMAMBADEPTH: Self-supervised Monocular Depth Estimation with Channel Mamba and Hybrid Attention

arXiv:2609.24494v1 Announce Type: new Abstract: Accurate monocular depth estimation serves as a core enabler for single camera scene understanding. However, existing self-supervised monocular depth es

local-aiarxiv-cs-cv

CNA: An AI-Oriented Comprehensive Normalized Assessment for Healthy Status and Application to Optimize RRT Strategies by Reinforcement Learning

arXiv:2609.22232v1 Announce Type: new Abstract: Millions worldwide require Renal Replacement Therapy (RRT) as a treatment essential for survival. However, optimizing RRT strategies via AI is challengi

Hardware

Co-occurrence Patterns of LoRA Adapters in Production Diffusion Model Inference Services

arXiv:2609.23321v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become a key technology for serving large-scale personalized large language models and diffusion models in the cloud. H

hardwarearxiv-cs-lg

Agents

CoaG: Cylinders on a Grid: Coarse 3D Layout Control for Video Generation

arXiv:2609.24208v1 Announce Type: new Abstract: We ask how little geometry a person has to draw to control both where people stand and where the camera moves in a generated video. Our answer is a grou

agentsarxiv-cs-cv

Cognition to Control - Multi-Agent Learning for Human-Humanoid Collaborative Transport

arXiv:2603.03768v2 Announce Type: replace Abstract: Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller changes th

safetyarxiv-cs-ro

Cognitive Action Reasoning for Proactive Robots from Human-Centered Multimodal Observations

model-releasesarxiv-cs-cv

arXiv:2609.23486v1 Announce Type: cross Abstract: Robots operating in human-centered environments are typically designed to execute explicit instructions, and most robot-learning datasets likewise pai

Collaborative Streaming Anomaly Detection with Interactive Explanations and Ensemble Consensus

arXiv:2609.23883v1 Announce Type: new Abstract: We present a collaborative streaming anomaly detection system for high-speed data streams that explicitly integrates human analysts into the decision lo

Collapse, Not Complexity: Failure-Conditioned Decomposition Repair for End-to-End Document Parsing

model-releasesarxiv-cs-cl

arXiv:2609.23592v1 Announce Type: cross Abstract: End-to-end document parsers increasingly offer an optional reasoning mode for complex pages. On a 180-page entropy-stratified discovery sample with on

Colon3R: Cross-Domain 3D Reconstruction from Monocular Colonoscopic Video

arXiv:2609.23961v1 Announce Type: new Abstract: Monocular colonoscopic 3D reconstruction is important for surgical robotic colonoscopy, but remains challenging due to weak texture, specular reflection

Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models

arXiv:2301.12254v5 Announce Type: replace-cross Abstract: Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive litera

Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.22896v1 Announce Type: new Abstract: Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo.

Tutorials

Common Cause, Not Cross-Attention: Blocking Visual Shortcuts in Audio-Video Generation

arXiv:2609.22361v1 Announce Type: new Abstract: Joint audio--video generators are trained on data in which what an event looks like and what it sounds like are strongly, often spuriously, correlated:

tutorialsarxiv-cs-lg

Commonsense-Grounded Path Planning from Abstract Instructions

model-releasesarxiv-cs-ro

arXiv:2609.22813v1 Announce Type: new Abstract: We present commonsense ranked search (CoRS), a novel path planner that turns an abstract instruction into a route that follows commonsense. While existi

Compact Low-Cost Hyperspectral Imaging via Angular-to-Spectral Diversity Conversion

arXiv:2609.23619v1 Announce Type: new Abstract: Snapshot hyperspectral imaging avoids sequential scanning, but systems that jointly achieve stable reconstruction, low cost, and compact optics remain l

Comparative Analysis of State-of-the-Art Foundation Models for Sleep Analysis Under Channel Reduction

arXiv:2609.22105v1 Announce Type: cross Abstract: Automatic sleep staging from polysomnography (PSG) is a well-studied task, but PSG itself is expensive, clinic-based, and burdensome to manually score

Comparative Performance and Parameter-Efficient Adaptation of DINOv2 for Active Trachoma Classification

model-releasesarxiv-cs-cv

arXiv:2609.23832v1 Announce Type: new Abstract: Automated grading of conjunctival photographs could reduce the cost and variability of trachoma prevalence surveys, but the relative value of modern pre

Comparative Study of Quantum and Classical Machine Learning Models in Binary Classification

arXiv:2609.23476v1 Announce Type: cross Abstract: A potential path forward is Quantum Machine Learning (QML), which aims to leverage quantum computing in conjunction with classical machine learning to

Comparing Latent Concept Formation in State Space Models and Transformers via Sparse Autoencoders

arXiv:2609.24440v1 Announce Type: new Abstract: The quadratic scaling of Transformer self-attention has driven the adoption of sub-quadratic Selective State Space Models (SSMs) like Mamba, which compr

safetyarxiv-cs-lg

Complementary rPPG-Derived and Lip-Region Frequency Cues for Talking-Face Deepfake Detection

arXiv:2609.22284v1 Announce Type: new Abstract: Talking-face (TF) deepfakes are detected unevenly by rPPG-based methods across generators. We study two lightweight visual-only cues, rPPG-derived wavef

Complex KDA: Understanding and Enhancing the Expressivity of Kimi Delta Attention

arXiv:2609.24797v1 Announce Type: new Abstract: Linear RNNs based on the delta-rule enable efficient sequence modeling, but their linear updates with a low-rank correction constrain their expressivity

Complex-valued Phase-Coherent Transformers

arXiv:2609.22415v1 Announce Type: new Abstract: Complex-valued Transformers have inherited softmax attention over the raw complex inner product. Outside natively complex domains this standard form sta

Complexities of Weak Proximal Oracle Methods for Composite Convex Optimization

arXiv:2609.24423v1 Announce Type: cross Abstract: We consider a standard convex composite optimization problem with either smooth or nonsmooth objective function, and under quadratic growth. In recent

Compound-QA: A Benchmark for Evaluating LLMs on Compound Questions

model-releasesarxiv-cs-cl

arXiv:2411.10163v3 Announce Type: replace Abstract: Large language models (LLMs) demonstrate remarkable performance across various tasks, prompting researchers to develop diverse evaluation benchmarks

Compressing 3D Gaussian Splatting via Cross-Representation Priors

arXiv:2609.23005v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality novel view synthesis but incurs high storage and transmission costs due to dense Gaussian primitives.

Agents

Computationally Efficient Density-Driven Optimal Control via Analytical KKT Reduction and Contractive MPC

arXiv:2603.18503v2 Announce Type: replace-cross Abstract: Efficient coordination for collective spatial distribution is a fundamental challenge in multi-agent systems. Prior research on Density-Driven

agentsarxiv-cs-ro

Computationally efficient safe exploration in reinforcement learning

arXiv:2609.22919v1 Announce Type: new Abstract: Reinforcement learning in real-life applications requires safety guarantees during exploration. Typical reinforcement learning algorithms do not provide

safetyarxiv-cs-lg

Applications

CompVLA: A Variable Compliance Vision-Language-Action Model for Contact-rich Manipulation

arXiv:2609.23614v1 Announce Type: new Abstract: Contact-rich manipulation, requiring robots to regulate not only motion but also how they yield to external forces, has emerged as the next frontier for

applicationsarxiv-cs-ro

Concurrency-Aware Process Model Forecasting with Causal Nets

arXiv:2609.22614v1 Announce Type: new Abstract: Process model forecasting (PMF) aims to predict the process model that will characterize a future period, thereby providing a process-level view of how

Confidence-Aware Teacher-Student Distillation for 3D Medical Segmentation

arXiv:2609.23815v1 Announce Type: new Abstract: Medical image segmentation models typically rely on large amounts of densely annotated volumetric data, limiting their scalability across tasks and imag

Agents

Conflicting Pattern Formation by Teams of Anonymous, Fully Disoriented Robots

arXiv:2609.23454v1 Announce Type: cross Abstract: Two groups of autonomous, anonymous, and oblivious mobile robots are deployed in the two-dimensional Euclidean plane, each assigned a distinct task. W

agentsarxiv-cs-ro

Conformal Robustness in Prediction-Driven Decision-Making

arXiv:2609.23170v1 Announce Type: cross Abstract: Modern prediction-driven decision systems often rely on black-box predictors, but a point forecast alone does not provide the uncertainty scale requir

Conformalized Quantile Regression and Minimax Limits of Fixed-Score Calibration under Known Covariate Shift

arXiv:2609.24929v1 Announce Type: cross Abstract: In this paper, we study nonasymptotic L^p error bounds for interval length and conditional coverage in split conformalized quantile regression (CQR).