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CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives

arXiv:2608.01725v1 Announce Type: cross Abstract: Modern computing and networking infrastructure emits telemetry continuously, yet operators convert it into decisions with a separate predictor per tas

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Certifying Plans under Model Mismatch: A Trilemma for Reachability from Scarce Data

DGX agent

arXiv:2608.02453v1 Announce Type: new Abstract: Sim-to-real policies are designed under nominal dynamics, but target-system trials may yield only a few isolated one-step transitions. We study pre-exec

model-releasesarxiv-cs-ro

4 Aug 2026

ChainVLA: Chaining Vision-Language-Action Queries through a Unified Execution State for Long-Horizon Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.02326v1 Announce Type: new Abstract: Humans perform long-horizon manipulation by retaining knowledge of what earlier actions have established while continuously adapting the motion underway

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

arXiv:2608.01968v1 Announce Type: new Abstract: Transformer models are most often understood through what they do: their benchmark performance, generation quality, or behavior on downstream tasks. Yet

Characterizing Bias in Post-Bandit Inference under Index Algorithms

arXiv:2608.01069v1 Announce Type: new Abstract: Bandit algorithms generate data for downstream inference, but adaptive sampling biases post-bandit sample means. We analyze this bias for stable index a

Characterizing Treatment-Context Medication Evidence Across Clinic Notes and Structured EHR Medication History

arXiv:2608.01570v1 Announce Type: new Abstract: Clinic notes and structured electronic health record (EHR) medication history often contain different medication information. Same-visit disagreement be

Chart Specification: Structural Representations for Incentivizing VLM Reasoning in Chart-to-Code Generation

arXiv:2602.10880v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have shown promise in generating plotting code from chart images, yet achieving structural fidelity remains challengin

ChordVideo: One-Step, Training-Free, Temporally Consistent Video Editing via Low-Energy Transport

arXiv:2608.00769v1 Announce Type: new Abstract: One-step text-to-image models enable training-free, inversion-free editing with only 1--2 network function evaluations (NFE), while ChordEdit stabilizes

safetyarxiv-cs-cv

CHOW-SLAM: Compact Hybrid Representation with Complementary Overlap Window Optimization for RGB-D SLAM

model-releasesarxiv-cs-cv

arXiv:2608.01914v1 Announce Type: new Abstract: Simultaneous localization and mapping (SLAM) based on Neural Radiance Fields (NeRF) enables dense, continuous scene reconstruction. However, existing sy

Applications

CLEAR: Conflict-aware Learning via Evidence-guided Adaptive Routing for Unified Sparse-View 3D Gaussian Super-Resolution

arXiv:2608.02206v1 Announce Type: new Abstract: Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and h

applicationsarxiv-cs-cv

Clear-Weighted Bit Allocation for Satellite Downlinks

arXiv:2608.01457v1 Announce Type: cross Abstract: Earth-observation satellites capture more imagery than intermittent ground contacts can transmit. Onboard systems threshold a cloud detector, discard

Applications

Climate-Dyna Deep Hedging for XVAs: Model-Based Reinforcement Learning, Residual Climate HVA, and Hedge-Instrument Discovery

arXiv:2608.01208v1 Announce Type: cross Abstract: For a trading desk, residual climate hedging valuation adjustment (HVA) is the climate cost left after its inherited hedge and any admissible overlay

applicationsarxiv-cs-lg

Cloud-ScPO: Hidden-State Geometry for Semi-Supervised Preference Optimization in LLM Reasoning

arXiv:2608.01014v1 Announce Type: new Abstract: Preference optimization improves mathematical reasoning in large language models (LLMs), but reliable chosen-rejected pairs usually require verified ans

Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization

arXiv:2608.01426v1 Announce Type: new Abstract: Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performan

CoLI: A Reproducible Platform for Continuum Robot Learning via Monolithic 3D Printing and Isomorphic Teleoperation

arXiv:2606.20389v2 Announce Type: replace Abstract: Continuum robots offer strong potential for manipulation tasks due to their high degrees of freedom, compliant structures, and operational safety. H

safetyarxiv-cs-ro

CompanionBench: A Theory-Anchored, Real-World-Grounded Benchmark for AI Emotional Companionship

model-releasesarxiv-cs-cl

arXiv:2608.02046v1 Announce Type: new Abstract: LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated. Existing benchmarks use hand-authored scenarios and pro

Comparing and Modeling Argumentation in German Political Communication across Arenas

arXiv:2608.00288v1 Announce Type: new Abstract: Deliberation, involving the formulation and exchange of arguments, forms an integral part of political decision making in democracies. Argumentation pat

safetyarxiv-cs-cl

Complete Motion Planning using Workspace-Fibered Decomposition for nR-Planar Manipulator

arXiv:2608.01172v1 Announce Type: new Abstract: We propose a workspace-fibered decomposition framework for motion planning in nR planar redundant manipulators operating in cluttered environments. Rath

researcharxiv-cs-ro

Compliant Sphere Lattice Contact: Distributed Contact Modeling for Sphere-Based Robot Representations

arXiv:2608.00263v1 Announce Type: new Abstract: Contact planning in robotics requires models that are both computationally efficient and physically accurate. Sphere-based robot representations satisfy

researcharxiv-cs-ro

Applications

Computational and Statistical Guarantees of the extit{c}-Rectified flow

arXiv:2608.02487v1 Announce Type: cross Abstract: Recently, rectified flow has emerged as a fundamental framework for large-scale image generation, powering state-of-the-art systems such as FLUX.1 and

applicationsarxiv-cs-lg

Computational Approaches to Understanding Large Language Model Impact on Writing and Information Ecosystems

arXiv:2506.17467v2 Announce Type: replace Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across soci

CoNav-UAV: Cooperative Dual-Altitude Aerial Navigation via Stackelberg Learning

model-releasesarxiv-cs-ro

arXiv:2608.01802v1 Announce Type: cross Abstract: Target-oriented vision-and-language navigation (VLN) on aerial platforms is attracting growing attention for missions such as disaster rescue, infrast

Conditional Deep Levy Models for Exotic Derivatives: History-Aware Path Generation and P-Q Payoff Diagnostics

arXiv:2509.13374v2 Announce Type: replace-cross Abstract: We develop and audit a history-aware financial path generator based on Denoising Levy Probabilistic Models (DLPMs) for conditional equity-inde

Conformal bandits: bringing statistical validity and reward efficiency under weak arm separability

arXiv:2512.09850v2 Announce Type: replace Abstract: We introduce Conformal Bandits, a novel framework integrating Conformal Prediction (CP) into bandit problems, a classic paradigm for sequential deci

Conformalized Large Language Models under Configuration Shift

arXiv:2608.01460v1 Announce Type: new Abstract: Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs)

Conservation laws determine what physical learning remembers

arXiv:2608.00097v1 Announce Type: cross Abstract: Physical learning rules such as equilibrium propagation (EP), coupled learning (CL), and adjoint coupled learning (AL) train resistive networks throug

Constrained Co-Design for Photonic Bayesian Neural Networks

arXiv:2608.02229v1 Announce Type: new Abstract: Classical neural networks frequently produce overconfident predictions on ambiguous or out-of-distribution (OOD) data, a liability that grows with each

Constructing Parallel Multidimensional Chromatic Lexicons for Corpus-Assisted Analysis of Russian and English Texts

arXiv:2608.01752v1 Announce Type: new Abstract: This article addresses the relative scarcity of research tools for the corpus-assisted linguistic analysis of colour terms in literary texts. It describ

Context-Aware Mixture of Domain Experts for Bodily Expression of Emotion in the Wild

arXiv:2608.02331v1 Announce Type: new Abstract: The same body posture can convey entirely different emotions depending on its surrounding context, yet most methods for recognising bodily emotions trea

Contextual Semantic Relevance Tracks fMRI BOLD Responses During Naturalistic Speech Comprehension

arXiv:2607.15856v2 Announce Type: replace Abstract: Naturalistic language comprehension requires listeners to process both local probabilistic expectations and contextual semantic relations. This stud

Control Under Compression: Reliability Frontiers for Tool-Using Agents

model-releasesarxiv-cs-cl

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

Convex Neural Energy Elements: Monolithic Finite-Element Assembly of Geometry-Parameterized Neural Operators with Stability and Error Guarantees

arXiv:2608.02036v1 Announce Type: new Abstract: Extending the neural-operator element method from individually trained, fixed-geometry neural elements to a library of reusable, geometry-parameterized

Cooperative Coevolution for Resource-Constrained Agentic LLM Post-Training

arXiv:2608.02391v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents produce long, multi-turn trajectories, making gradient-based post-training memory-intensive. Evolution st

CopyCat: Improving Fine-Grained Subject Consistency in Subject-to-Image Models within Seconds

arXiv:2608.00674v1 Announce Type: new Abstract: Recent subject-to-image models have achieved impressive progress in personalized image generation, yet they still struggle to preserve fine-grained subj

CoRe-GNN: Multilevel Message passing on Coarsened graphs

arXiv:2608.02128v1 Announce Type: new Abstract: Training Graph Neural Networks on large graphs is challenged by the memory cost of storing all node representations across layers. We show that several

CORTIVA: Candidate-Score Fusion of Complementary Visual Teachers for EEG- and MEG-to-Image Retrieval

model-releasesarxiv-cs-cv

arXiv:2608.01355v1 Announce Type: new Abstract: Decoding visual experience from non-invasive brain activity is central to neuroscience and brain-computer interfaces. Functional magnetic resonance imag

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

model-releasesarxiv-cs-cl

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

CoSynFlow: Conformal Symplectic Neural Flows for Cross-System Prediction of Dissipative Hamiltonian Dynamics

arXiv:2608.00571v1 Announce Type: new Abstract: Learning solution operators for differential equations is a central problem in scientific machine learning. However, many neural operator methods optimi

Tutorials

CoT-Edit: Let CoT Guide Instruction Video Editing

arXiv:2608.01113v1 Announce Type: new Abstract: Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relation

tutorialsarxiv-cs-cv

Counting the Cost of War Under Satellite Embargo: Zero-Shot Estimation of Impacted Infrastructure

arXiv:2608.00119v1 Announce Type: new Abstract: Rapid estimation of impacted structures - critical for conflict-zone humanitarian response - is frequently hindered by post-strike satellite data embarg

safetyarxiv-cs-cv

CountTRuCoLa: Rule Learning for Interpretable Temporal Knowledge Graph Forecasting

arXiv:2509.09474v2 Announce Type: replace Abstract: We address the task of temporal knowledge graph forecasting with an inherently interpretable method based on symbolic rules. Motivated by recent wor

Tutorials

Coverage-Driven Adaptive Keyframe Selection for Video Understanding

arXiv:2608.00714v1 Announce Type: new Abstract: Recent advances in large vision-language models (LVLMs) have enabled long-video understanding and analysis. However, processing the large number of fram

tutorialsarxiv-cs-cv

CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs

arXiv:2608.02578v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing th

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.01644v1 Announce Type: new Abstract: In video understanding, vision-language models (VLMs) must ingest massive numbers of visual tokens, causing the computational and memory cost of the pre

Agents

Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning

arXiv:2505.08630v2 Announce Type: replace Abstract: Training cooperative agents in sparse-reward scenarios poses significant challenges for multi-agent reinforcement learning (MARL). Without clear fee

agentsarxiv-cs-lg

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception

arXiv:2608.01055v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly expected to solve structured perception tasks that require visual recognition, language-to-obj

CRIP: Channel Level Representation Injection for Personalized One-Shot Federated Learning

arXiv:2608.02222v1 Announce Type: new Abstract: One-shot federated learning (OSFL) has emerged as a promising collaborative model learning framework with only a single round of communication, offering

CriPO: Enhancing Rubric-based RL via Self-Distillation

arXiv:2607.18082v3 Announce Type: replace Abstract: Rubric-based RL has recently shown promise in improving LLMs on open-ended tasks. A widely recognized limitation of rubric-based RL is limited explo