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Chasing Label Shifters: A Change-Aware Framework for Dynamic Graph Node Classification

arXiv:2610.17582v1 Announce Type: new Abstract: Entities in real-world systems often evolve over time: users shift between information consumption patterns, researchers migrate between fields, and fir

applicationsarxiv-cs-lg

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Checking the Checkers: A Synthesis of Verifier Noise and Robustness in RLVR

DGX agent

arXiv:2610.17824v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a principal recipe for improving the reasoning of large language models (LLMs). It rest

safetyarxiv-cs-lg

14 Oct 2026

ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning

arXiv:2610.17183v1 Announce Type: cross Abstract: Current chemistry benchmarks primarily evaluate outcome prediction or reaction pathway generation, but rarely test whether a model can explain why an

ChronoScribe: Semantic-Numerical Specialization for Instruction-Driven Time Series Forecasting

arXiv:2610.16345v1 Announce Type: cross Abstract: Recent advances in instruction-driven time series forecasting highlight a fundamental tension: systems must simultaneously master natural-language ins

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

ChunkAct: Action Chunking for Agentic Robotics

arXiv:2610.18874v1 Announce Type: cross Abstract: Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action

CineMem: Attention-Aligned Fine-grained Memory Retrieval for Multi-Shot Long Video Generation

arXiv:2610.17926v1 Announce Type: new Abstract: Autoregressive video generation relies on memory retrieval to model long-range dependencies. This capability becomes particularly critical for multi-sho

CineRecon: Benchmarking Frontier Models for Agentic Cinematic Reconstruction

arXiv:2610.16577v1 Announce Type: new Abstract: Reconstructing reference videos as editable dynamic 3D scenes is an important path toward controllable video generation for filmmaking: these scenes pro

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

arXiv:2506.17585v4 Announce Type: replace-cross Abstract: Large language models can answer questions correctly and still hallucinate their citations. Most citation systems address this by retrieving d

Agents

CityCode: Building Agent-Operable 3D Cities from Sparse Aerial Observations

arXiv:2610.18342v1 Announce Type: new Abstract: Urban spatial intelligence calls for 3D cities that agents can measure, interpret, and modify across successive tasks. Maintaining such cities as persis

agentsarxiv-cs-cv

CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks

arXiv:2610.15327v1 Announce Type: cross Abstract: Removing audio can shift a visual predictor's output without showing whether the task uses the intended audio information. We introduce Conditional In

Class-Conditional Conformal Prediction for Signal Temporal Logic Inference with Many Classes

arXiv:2610.14352v1 Announce Type: new Abstract: Signal Temporal Logic (STL) inference provides interpretable formulas for time series classification. For multiclass classification, however, accurate p

ClearNav: Perception-Aligned Quadrotor Flight Using Differential-Physics

arXiv:2610.17419v1 Announce Type: cross Abstract: Autonomous quadrotor flight in cluttered environment is an key capability for tasks like inspection and search. Navigation policies trained in simulat

Clinical value claims in multimodal AI outpace supporting evidence

arXiv:2610.14395v1 Announce Type: new Abstract: Multimodal prediction models add a data source, such as imaging or an assay, to clinical information, and health systems must decide whether that added

CLNO: Conservative Local Neural Operator for Compressible Flow Prediction

arXiv:2610.16040v1 Announce Type: cross Abstract: We propose a conservative local neural operator (CLNO) for accurate and generalizable autoregressive prediction of compressible flows. Building upon t

Tutorials

CloneOT: predicting clone-specific perturbation responses with lineage-supervised neural inverse optimal transport

arXiv:2610.16093v1 Announce Type: cross Abstract: Predicting single-cell perturbation responses requires mapping between two unpaired populations of cells measured before and after the perturbation. O

tutorialsarxiv-cs-lg

Closing the Estimation Gap: Training-Free Transductive Inference for Cross-Domain Few-Shot Action Recognition

arXiv:2610.18209v1 Announce Type: new Abstract: Cross-domain few-shot action recognition (CD-FSAR) aims to recognise unseen action classes in a target domain from a handful of labelled videos. Despite

ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion

arXiv:2610.16293v1 Announce Type: new Abstract: Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicke

ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction

arXiv:2610.14200v1 Announce Type: cross Abstract: We introduce ClothCode, a unified generative framework for garment state estimation and action-conditioned dynamics prediction in a shared discrete co

applicationsarxiv-cs-cv

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI

arXiv:2506.15468v2 Announce Type: replace-cross Abstract: We propose co-creative learning as a novel paradigm where humans and AI, i.e., biological and artificial agents, mutually integrate their part

Co-DSL: Human-LLM Co-design of Reusable Spatial Concepts for Layout Generation

arXiv:2610.15290v1 Announce Type: cross Abstract: We present Co-DSL, a framework in which users and LLMs co-design reusable spatial concepts for layout generation. In the first stage, our system allow

Coarse-Graining Recursive Expert Computation: Continuation-Relative Interfaces and Failure Modes

arXiv:2610.14413v1 Announce Type: new Abstract: Computational coarse-graining aims to replace a sequence of updates with a cheaper module while preserving task performance. We present a continuation-r

CoCA: Criterion-Aware Credit Assignment for Rubric-Based Reinforcement Learning

arXiv:2610.17733v1 Announce Type: new Abstract: Rubric-based reinforcement learning (RL) evaluates responses against explicit criteria to construct rewards, offering a viable way to train large langua

Code-Interactive Visual Reasoning for Financial Candlestick Understanding

arXiv:2610.16587v1 Announce Type: new Abstract: Financial candlestick understanding requires locating visual elements, aligning them across trading dates and panels, and combining observations through

Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation

arXiv:2610.17651v1 Announce Type: cross Abstract: Recent coding large language models (LLMs) can synthesize dynamic 4D worlds from natural language, but the resulting content remains a visual artifact

CodeLift: Your Test Suite Is Secretly a Dense SWE Curriculum

arXiv:2610.17224v1 Announce Type: new Abstract: The pass-all-test binary reward has become a standard recipe for training software engineering agents, but its sparsity eliminates difference of partial

CodeWalk: Generating Coding Benchmarks by Walking a Problem Graph

arXiv:2610.15345v1 Announce Type: new Abstract: High-quality coding problems are expensive to collect. Benchmarks such as SWE-bench rely on substantial human curation, while synthetic alternatives typ

Tutorials

Coding LLMs Can Be Harnessed to Learn Interpretable Models from Data

arXiv:2610.14006v1 Announce Type: new Abstract: Since compact, interpretable classifiers correspond to simple programs, it is natural to ask if LLM-based coding agents can be used to learn interpretab

tutorialsarxiv-cs-lg

Agents

CoEvoke: Evoking Multi-Agent Collaboration for Trajectory Collection

arXiv:2610.14021v1 Announce Type: new Abstract: Training multi-agent collaboration requires trajectories of checking, feedback, and repair, yet task-solving rollouts may end in immediate approval or r

agentsarxiv-cs-lg

Agents

CoLA: Multi-VLA Coordination via Learned Adapters

arXiv:2610.15337v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are typically deployed as isolated single-agent policies. When several such agents share a workspace, they can coo

agentsarxiv-cs-lg

Collaborative Planning for UAV-UGV Teams under Operational Constraints via Masked Error-bounded Neuro-Symbolic Diffusion

arXiv:2610.18850v1 Announce Type: new Abstract: Collaborative planning under operational constraints is essential for heterogeneous robot teams in large-scale missions. Unmanned Aerial Vehicles (UAVs)

safetyarxiv-cs-ro

Colored Graph Signal Diffusion Models

arXiv:2610.17282v1 Announce Type: cross Abstract: Standard diffusion processes with isotropic noise corruption are not spectrally neutral. They inherit a coarse-to-fine generation hierarchy from the n

Comparative Study of Canvas- and Coordinate-Based Geometry-Conditioned Neural Networks for Real-Time Prediction of Indoor Environments with Varying Room Dimensions

arXiv:2610.15885v1 Announce Type: cross Abstract: Computational fluid dynamics (CFD) is computationally expensive for iterative building design. Deep learning surrogates offer faster predictions, but

Comparing GenAI to Machine Learning and Manual Review for eDiscovery

arXiv:2610.16925v1 Announce Type: new Abstract: Keeling et al. [Keeling2026Generative] report on a case study recently conducted by Redgrave LLP in which they assert that Relativity's Generative AI Re

applicationsarxiv-cs-lg

COMPASS: Contextual Moment Prior Alignment for Generalizable AIGI Detection

arXiv:2610.18034v1 Announce Type: new Abstract: Generalizable AI-generated image (AIGI) and deepfake detection remain challenging due to the asymmetry phenomenon, where adaptation to limited training

safetyarxiv-cs-cv

COMPASS: Membership Inference Attack Against Vision Large Language Models via Adaptive Noise Calibration

arXiv:2610.17332v1 Announce Type: new Abstract: Vision large language models (VLLMs) are deployed in privacy-sensitive domains, raising training-data exposure concerns. Existing gray-box membership in

Hardware

Competition Domains Matter: Selective Head Globalization for Training-Free Sparse Attention in Video Diffusion Transformers

arXiv:2610.14672v1 Announce Type: new Abstract: Training-free sparse attention is a practical route to efficient video diffusion transformer inference, yet existing methods typically fix the competiti

hardwarearxiv-cs-cv

Competitive Task Allocation with Temporal Proposal Windows and Improved Artificial Potential Fields for Dual-Arm Industrial Manipulation

arXiv:2610.15763v1 Announce Type: new Abstract: Modern industrial automation demands autonomous collaborative systems capable of coordinated manipulation in workspaces with heterogeneous object arrang

safetyarxiv-cs-ro

Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method

arXiv:2510.23149v2 Announce Type: replace-cross Abstract: Physics-informed statistical learning (PISL) integrates empirical data with physical knowledge to enhance the statistical performance of estim

Composable Dynamics for Cooperative Humanoids: A RoboCompiler Extension

arXiv:2610.14237v1 Announce Type: new Abstract: Physically connected humanoids need consistent dynamics for internal actuator loops, inter-robot forces, and changing ground supports. We extend RoboCom

researcharxiv-cs-ro

Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learning

arXiv:2610.14941v1 Announce Type: new Abstract: Diffusion-based policies have recently emerged as a powerful paradigm for offline reinforcement learning, but their reliance on multi-step denoising int

Compositional Concepts Erasing: Disentangling Object-Style via Domain Manifold Unlearning

arXiv:2610.14514v1 Announce Type: new Abstract: Diffusion models pose significant risks regarding the generation of illicit content and copyright violations. This has catalyzed the development of mach

Compositional RL: Evaluating and Training LLMs for Collaborative Reasoning

arXiv:2610.17456v1 Announce Type: cross Abstract: Language models are often evaluated alone but increasingly deployed together, routed between, made to debate, ensembled, or collaboratively trained. F

Tutorials

Comprehensive Workflow for Uncertainty-Aware Ionic Liquid Solvent Discovery

arXiv:2610.17171v1 Announce Type: cross Abstract: Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well s

tutorialsarxiv-cs-lg

Compression Through Time: An Interplay of Separability, Stationarity and Capacity

arXiv:2610.16660v1 Announce Type: new Abstract: Information-theoretic and geometric compression have been widely studied as possible explanations for generalization. Yet their temporal dynamics in rec

applicationsarxiv-cs-lg

Compute-optimal data scaling for neural surrogates via multi-fidelity training

arXiv:2610.17221v1 Announce Type: new Abstract: Neural surrogates for Partial Differential Equations (PDEs) are usually trained on synthetic data from numerical simulators. As models grow and scaling

Compute-Optimal Scaling Laws for Spiking Language Models

arXiv:2610.15146v1 Announce Type: new Abstract: Spiking neural networks target energy-efficient language modeling through sparse, binary activations, but the efficiency-accuracy tradeoff of spiking la

Concealed Handgun Detection using WiFi Signals

arXiv:2610.18736v1 Announce Type: new Abstract: While conventional camera-based surveillance systems and metal detectors can provide a sufficient level of security when used appropriately, they have f