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Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

arXiv:2609.01818v1 Announce Type: cross Abstract: The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the cl

local-aiarxiv-cs-ai

3 Sept 2026

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ZipTok3D: High-Fidelity 3D Tokenization with Compact Token Prefixes

DGX agent

arXiv:2609.01740v1 Announce Type: new Abstract: Compact token sequences are essential for efficient 3D generation. However, existing 3D tokenizers typically organize latent representations either over

model-releasesarxiv-cs-cv

3 Sept 2026

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients

model-releasesarxiv-cs-cl

arXiv:2606.18216v2 Announce Type: replace Abstract: Knowledge distillation transfers a teacher's competence to a small student but is brittle in the small-student regime: forcing the student to imitat

3 Sept 2026

3D-Consistent Multi-View Editing by Correspondence Guidance

arXiv:2511.22228v3 Announce Type: replace-cross Abstract: Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently of

researcharxiv-cs-ai

A Benchmark for Vehicle Attribute Classification in Cross-Domain Surveillance Scenarios

arXiv:2609.01584v1 Announce Type: new Abstract: Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traff

A Certificate-Producing Cascade for Equational Implication: The SAIR EQT2 Stage 2 Solver

arXiv:2609.00706v1 Announce Type: new Abstract: The SAIR Mathematics Distillation Challenge on Equational Theories asks a solver to classify whether one magma identity implies another and, for either

local-aiarxiv-cs-cl

A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling

arXiv:2609.00847v1 Announce Type: cross Abstract: As machine learning and artificial intelligence find their way into nearly every aspect of climate, weather, and Earth system modeling, it is worth pa

researcharxiv-cs-ai

A Classifier That Teaches Itself: Self-Improving, Frozen-gate Training (SIFT) for Dynamic Document Classification

arXiv:2607.18358v2 Announce Type: replace Abstract: Document classification is a solved problem in the laboratory and an unsolved one in the enterprise. The blocker is rarely model architecture; it is

safetyarxiv-cs-cl

A Closed-Loop Evaluation of Capability Loss and Recovery in Compressed Driving Policies

arXiv:2609.00718v1 Announce Type: new Abstract: Many automobile and mobility companies deploy learned driving policies on embedded computers with limited memory and power. Pruning, knowledge distillat

safetyarxiv-cs-ai

A Compact Robotic Finger with 2-DoF MCP Joint Embedding DoF-Selective Passive Continuously Variable Transmission for Wide Force-Speed Operating Range

arXiv:2609.00769v1 Announce Type: new Abstract: This letter presents a compact two-degree-of-freedom (DoF) robotic finger with a flexion-selective passive continuously variable transmission (CVT) to a

agentsarxiv-cs-ro

Hardware

A Composable Evaluation System for Reproducible Omni-Modal Foundation Model Evaluation

arXiv:2609.01315v1 Announce Type: new Abstract: Building an omni-modal foundation model means evaluating it across text, image, video, and audio. Excellent evaluation toolkits exist for each modality,

hardwarearxiv-cs-ai

A Compositional Kernel Model for Feature Learning

arXiv:2509.14158v3 Announce Type: replace Abstract: We study a compositional variant of kernel ridge regression in which the predictor is applied to a coordinate-wise reweighting of the inputs. Formul

researcharxiv-cs-lg

A Cone-Constrained Bilinear Decomposition for Total Scaled-Gradient Variation Models

arXiv:2609.00036v1 Announce Type: new Abstract: The total scaled-gradient variation (TSGV) regularizer, derived from sparse modeling of piecewise-linear structures, has been shown to preserve edges an

A convolutional framework for detecting event-driven dynamics in energy price series

arXiv:2609.00402v1 Announce Type: cross Abstract: This paper develops a general convolutional neural network (CNN) framework for detecting heterogeneous event-driven dynamics in univariate time series

researcharxiv-cs-lg

A Dataset for Modeling Iterative Problem-Solving

model-releasesarxiv-cs-cl

arXiv:2609.00940v1 Announce Type: new Abstract: Solving problems through repeated attempts is a sequential modeling task: at each step, the solver receives feedback and decides how to revise their sol

A Formal Analysis of Agent Payment Protocols

arXiv:2609.00060v1 Announce Type: cross Abstract: Agent payment protocols are emerging as a key transaction layer for autonomous commerce, enabling AI agents to purchase goods and services and execute

agentsarxiv-cs-ai

A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss

arXiv:2609.00591v1 Announce Type: new Abstract: An image may be worth a thousand words, but most captioning models describe it in only a few. Modern vision-language models produce fluent high-level ca

local-aiarxiv-cs-cv

A Human-AI Theorem Connecting Spontaneous and Field-Induced Mechanisms of Collective Behavior in One Dimension

arXiv:2609.00322v1 Announce Type: cross Abstract: Can an artificial intelligence (AI) generate a scientific hypothesis outside a human collaborator's active hypothesis space (AHS), and can human-AI re

agentsarxiv-cs-ai

A Hybrid Insider Threat Detection Framework Combining Multi-Agent Simulation, Layered SIEM Correlation, and Theory-of-Mind Reasoning

arXiv:2601.04243v2 Announce Type: replace-cross Abstract: This paper presents a hybrid insider threat detection framework for enterprise environments, integrating multi-agent simulation, layered SIEM

agentsarxiv-cs-ai

A hybrid quantum-classical neural network for learning to route

model-releasesarxiv-cs-lg

arXiv:2609.00489v1 Announce Type: new Abstract: This work studies hybrid quantum-classical neural networks for learning routing heuristics. Specifically, this paper asks whether small quantum neural n

A Lagrangian View of Flow Matching

arXiv:2609.00198v1 Announce Type: new Abstract: Modern explicit-time generative models, such as Flow Matching [Lipman et al., 2023] and Rectified Flow [Liu et al., 2023], are typically derived top-dow

researcharxiv-cs-cv

Applications

A Machine Learning-Driven Solution for Denoising Inertial Confinement Fusion Images

arXiv:2511.16717v3 Announce Type: replace-cross Abstract: Neutron imaging is essential for diagnosing and optimizing inertial confinement fusion implosions at the National Ignition Facility. Due to th

applicationsarxiv-cs-ai

Applications

A Mathematical Framework for Legacy, Governance, and Decision Integrity in Enterprise AI

arXiv:2609.00572v1 Announce Type: cross Abstract: Enterprise artificial intelligence is increasingly embedded in decisions that must remain lawful, explainable, adaptable, and accountable despite pers

applicationsarxiv-cs-ai

A Mathematical Theory of Reusable Neural Bases for Network Compression

model-releasesarxiv-cs-ai

arXiv:2609.01550v1 Announce Type: cross Abstract: As large AI models become increasingly prevalent across a wide range of applications, memory cost has become a critical bottleneck in both training an

A Multi-Branch Feature Fusion Approach for Health Misinformation Detection and Propagation

model-releasesarxiv-cs-lg

arXiv:2609.00403v1 Announce Type: new Abstract: This paper presents a multi-branch fusion framework for detecting and characterising the propagation of health misinformation in online social networks

A multicenter benchmark and clinically structured metric for coronary CTA report generation

arXiv:2609.00909v1 Announce Type: new Abstract: Reliable evaluation of automated coronary computed tomography angiography (CCTA) report generation requires standardized multicentre benchmarks and clin

Tutorials

A Network Science Perspective on Evaluating Deep Graph Generative Models

arXiv:2609.01015v1 Announce Type: cross Abstract: Traditional network models from network science, such as the Erdos-Renyi and configuration models, generate random networks that reproduce few selecte

tutorialsarxiv-cs-ai

A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data

arXiv:2609.01514v1 Announce Type: cross Abstract: Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of chea

researcharxiv-cs-cv

A Stable Aggregation Method for Quantum Federated Learning

model-releasesarxiv-cs-ai

arXiv:2609.00356v1 Announce Type: new Abstract: Quantum federated learning (QFL) enables clients to train quantum neural network (QNN) models without sharing private data. We find that aggregation in

A Study of Hidden-State Optimization Order in Predictive Coding Networks

arXiv:2609.00686v1 Announce Type: cross Abstract: Local learning methods offer an alternative to end-to-end backpropagation, but their unstructured local objectives can produce weak feature learning i

local-aiarxiv-cs-ai

A systematic Approach to constructing a Chance-and-Risk Matrix for Semiconductor Supply Chains

arXiv:2609.01563v1 Announce Type: new Abstract: Semiconductor supply chains face escalating risks from geopolitical tensions, geographic concentration, and rapid technological shifts, yet no scalable

researcharxiv-cs-cl

A Text Recognition Dataset from Sahidic Coptic Ancient Manuscripts

arXiv:2606.15987v2 Announce Type: replace Abstract: In this work, we target Handwritten Text Recognition (HTR) in low-resource scenarios, which arise from underrepresented languages, rare scripts, and

A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone

model-releasesarxiv-cs-ai

arXiv:2505.12781v5 Announce Type: replace-cross Abstract: Training high-performing Small Language Models (SLMs) remains costly, even with knowledge distillation and pruning from larger teacher models.

A Unified Mechanistic Analysis of Knowledge- and Safety-Based Refusals

arXiv:2609.00760v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly trained to decline queries that fall outside their knowledge (knowledge-based refusal, KR) or violate safe

safetyarxiv-cs-cl

A Wearable Pneumatic Device for Continuous, Closed-Loop, Bidirectional Tactile Interaction

arXiv:2609.00612v1 Announce Type: new Abstract: We present a system of two wearable pneumatic haptic devices that supports continuous, closed-loop, bidirectional tactile interaction at perceptually re

researcharxiv-cs-ro

Accelerating Chemical Kinetics for Exoplanet Atmospheres using Neural Networks

model-releasesarxiv-cs-lg

arXiv:2609.00428v1 Announce Type: cross Abstract: Observations increasingly reveal the coupled radiative, chemical, and dynamical processes that shape exoplanet atmospheres. Interpreting these atmosph

Accelerating Reinforcement Learning via MPC Solver-Gradient Guidance for Weights-varying MPC

arXiv:2609.01061v1 Announce Type: cross Abstract: In Model Predictive Control (MPC), cost-function weights shape closed-loop behavior, yet changing conditions often make fixed parametrizations subopti

safetyarxiv-cs-lg

Accurate Reconstruction of Gas Turbine Blade Geometry Using 3D/2D Rigid Registration and CT View Optimization

arXiv:2609.01368v1 Announce Type: new Abstract: Non-destructive X-ray and computed tomography (CT) testing are essential for ensuring the dimensional accuracy of manufactured components with complex i

safetyarxiv-cs-cv

ADAPT: Agile Diffusion Action Priors for Robust and Steerable Online Text-Driven Humanoid Control

arXiv:2609.00677v1 Announce Type: new Abstract: We present ADAPT, an end-to-end framework for interactive, text-conditioned humanoid whole-body control. Unlike dominant text-to-motion pipelines that g

safetyarxiv-cs-ro

Adapting Without Gradients: Affine Statistics Transport and What Its Certificate Can Tell You

arXiv:2609.00374v1 Announce Type: cross Abstract: Test-time adaptation (TTA) typically assumes that model parameters can be updated at inference time. This assumption is restrictive for inference-only

safetyarxiv-cs-ai

Adaptive Collision Sensitivity for Efficient and Safe Human-Robot Collaboration

arXiv:2409.20184v3 Announce Type: replace Abstract: What is considered safe for a robot operator during physical human-robot collaboration (HRC) is specified in corresponding HRC standards (e.g., ISO

researcharxiv-cs-ro

Applications

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

arXiv:2609.01601v1 Announce Type: cross Abstract: The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repos

applicationsarxiv-cs-ai

Adaptive Depth-Map-Guided Bundle Adjustment for Correspondence-Free Multi-View Point Cloud Registration

arXiv:2609.01089v1 Announce Type: new Abstract: Robotic processing of irregular steel scrap requires dense 3-D measurement to replace manual visual assessment in hazardous cutting workcells. The recon

researcharxiv-cs-ro

AdaptNTK: Adaptive Uncertainty Quantification and Active Learning for Neural Network Potentials

arXiv:2609.00488v1 Announce Type: new Abstract: Machine learning interatomic potentials bridge the gap between quantum chemical precision and classical computational speed, enabling molecular dynamics

researcharxiv-cs-lg

AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning

arXiv:2512.16883v2 Announce Type: replace Abstract: Equipping large language models (LLMs) with search engines via reinforcement learning (RL) promises effective search agents. However, adaptively bal

researcharxiv-cs-cl

Tutorials

ADGNet: Asymmetric Dual-text Guided Network for Infrared Small Target Detection

arXiv:2609.00853v1 Announce Type: cross Abstract: InfRared Small Target Detection (IRSTD) is a challenging task. Relying solely on pixel-level information, vision-only methods struggle to distinguish

tutorialsarxiv-cs-ai

Advanced Pixel Diffusion Model with Guided Sparse Global Refinement

arXiv:2609.00798v1 Announce Type: new Abstract: Pixel-space diffusion has recently emerged as a promising direction for high-fidelity image generation by modeling images directly in the original pixel

researcharxiv-cs-cv

Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models

arXiv:2509.25050v2 Announce Type: replace Abstract: Reinforcement Learning (RL) has emerged as a central paradigm for advancing Large Language Models (LLMs), where both pre-training and RL post-traini

safetyarxiv-cs-lg