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arXiv:2601.14628v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit powerful semantic representations from large language models, but carrying over their design priorities

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ObsSpec: Accelerating Agentic Reinforcement Learning with Observation Speculation

DGX agent

arXiv:2610.15246v1 Announce Type: new Abstract: Tool-using agents alternate between model generation and tool execution, waiting for each tool call to complete before starting the next generation. Thi

safetyarxiv-cs-lg

14 Oct 2026

OpenDGO: Benchmarking Multi-Agent Organizations Across Diverse Application Domains

arXiv:2610.17143v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems are increasingly applied across diverse domains, yet different applications require different forms

PATTERN Can Be Solved from Memory: Generator-Aware Baselines for Synthetic Node Classification

arXiv:2610.15020v1 Announce Type: new Abstract: PATTERN, a synthetic node-classification benchmark still used to rank graph networks, plants a random subgraph in a random host graph and asks which nod

PhaseQuant: Mitigating Activation Quantization Collapse via Residual-Stream Dynamics

arXiv:2606.12487v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is essential for efficient large language model (LLM) inference, but reliably quantizing activations remains challe

Physical SLAM: Physics-aware Simultaneous Localisation and Mapping

model-releasesarxiv-cs-ro

arXiv:2610.17260v1 Announce Type: new Abstract: To reconstruct a predictive 4D representation of the physical world from monocular video captured by a moving camera, we jointly reconstruct dynamic Gau

Physics-guided machine learning for saturation control across variable hydraulic conditions in heap leaching

arXiv:2610.15947v1 Announce Type: cross Abstract: Heap-leaching hydraulics vary between regions of an ore bed, motivating fast prediction models that accommodate different material properties. This st

PhysicsSliders: Learning Physical Controls for Audio Foley Generation

arXiv:2610.18597v1 Announce Type: cross Abstract: Physical properties provide intuitive controls for sounds made by interacting objects. The challenge is to make a generative model respond predictably

Tutorials

PING: physics informed graph neural network for advection-diffusion processes with applications to solar power forecasting

arXiv:2610.18280v1 Announce Type: new Abstract: Advection-diffusion plays an essential role in transport phenomena such as atmospheric and cloud dynamics. Improved forecasting of cloud motion, in turn

tutorialsarxiv-cs-lg

PolUR: Polarization Aware Multimodal Degradation Perception for Underwater Image Restoration

arXiv:2610.17991v1 Announce Type: new Abstract: Recovering high-quality images from degraded underwater observations is crucial for underwater exploration. Polarization observations show promise as an

Tutorials

Pro-t-VAE: Closed-Form Student's t Mixtures for Robust Prototype Discovery

arXiv:2610.14894v1 Announce Type: new Abstract: We present a robust deep generative framework for unsupervised image prototype discovery, built on a heavy-tailed Student's t mixture prior, that bridge

tutorialsarxiv-cs-lg

Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors

arXiv:2610.18607v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful generative priors for extreme image compression, but their stochastic, iterative generation processes are n

ReDiS: Reasoning-Diagnosis Self-Evolution for Multimodal Reasoning in Remote Sensing

arXiv:2610.18388v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown strong potential for remote sensing understanding, yet reliable reasoning remains challenging when t

RSAJEV: Training-Free Abstaining Prototype Memory for Eliminating Silent Hallucination in JEV-Based Remote Sensing Classification

arXiv:2610.15742v1 Announce Type: new Abstract: Scene classification of remote sensing imagery with multimodal large language models (MLLMs) is formulated as a single-forward-pass decision problem: ca

Safety

SARATHI: Decoupled Data-Free Probing and Adaptive Reconstruction for Structured LLM Pruning

arXiv:2610.15514v1 Announce Type: new Abstract: Structured pruning reduces the inference cost of large language models (LLMs) by permanently removing neurons and weight rows, yielding dense, hardware-

safetyarxiv-cs-lg

Scalable Identification of Physics-Based and Neural Dynamics from Partial Measurements

arXiv:2610.16559v1 Announce Type: cross Abstract: We present a scalable method for identifying nonlinear dynamics from partial measurements, supporting physics-based, neural-network, and gray-box mode

ScenePercept: Scenario-Conditioned Perceptual Assessment of Real-World User-Generated Content Images

arXiv:2610.17661v1 Announce Type: new Abstract: The rapid development of mobile imaging and social platforms has led to explosive growth in user-generated content images, making their systematic and c

Safety

Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs

arXiv:2610.14094v1 Announce Type: new Abstract: Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially cons

safetyarxiv-cs-cv

SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference

arXiv:2610.17146v1 Announce Type: cross Abstract: Bayesian predictive regions account for parameter uncertainty but can be poorly calibrated under model misspecification, even with expensive full MCMC

Separating Prompt Harmfulness from Interaction Safety via Partial Generation

arXiv:2610.16761v1 Announce Type: cross Abstract: LLM-based information systems need safety guardrails. Most guardrails classify the prompt alone. If the prompt looks harmful, the system rejects it be

Sequence-Structured Decision Learning for Branch-and-Bound in Mixed-Integer Linear Programming

arXiv:2610.14835v1 Announce Type: new Abstract: Branch-and-bound (BnB) solves mixed-integer linear programs by constructing and exploring a search tree. Node selection and branching are two recurrent

ShoeFit: A New Dataset and Dual-image-stream DiT Framework for Virtual Footwear Try-On

arXiv:2610.18325v1 Announce Type: new Abstract: Virtual footwear try-on (VFTON), a critical yet underexplored area in virtual try-on (VTON), aims to synthesize faithful try-on results given diverse fo

Skin Tone in the Wild: A Dataset and Benchmark for 10-tone MST Classification

arXiv:2603.02475v2 Announce Type: replace Abstract: Skin tone classification is a fundamental task in computer vision, with applications in quantifying medical features, assessing demographic represen

SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy

arXiv:2610.17323v1 Announce Type: new Abstract: Face recognition systems are deployed widely enough that a photograph shared online can be matched without its subject's consent. Generator-based protec

TAG: Calibrating SAM3 for Universal Image Segmentation without Dense Supervision

arXiv:2610.14651v1 Announce Type: new Abstract: The recent Segment Anything Model 3 (SAM3) extends powerful promptable segmentation from spatial cues to concepts, raising the prospect of a single foun

Text-Vision Co-Instructed Image Editing

arXiv:2606.16767v2 Announce Type: replace Abstract: Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are se

The Value of Being Wrong: Self-Mined Visual In-Context Learning from Errors

arXiv:2610.16977v1 Announce Type: new Abstract: Visual in-context learning (ICL) enables vision-language models (VLMs) to adapt at test time via demonstration examples, but its effectiveness depends c

Tiny Recursive Message Passing

arXiv:2610.18649v1 Announce Type: new Abstract: Message passing neural networks have shown remarkable performance in algorithmic and constraint reasoning, due to their ability to encode the structure

To Defer or Not to Defer? Online Learning with LLMs and Congested Experts

arXiv:2610.15128v1 Announce Type: new Abstract: Modern AI systems increasingly combine large language models (LLMs) with human experts, using the LLM to handle routine queries while deferring uncertai

Applications

TokenPB: Enabling VLA Action Self-Verification via VLM Token Probability Bucketing

arXiv:2603.18091v2 Announce Type: replace Abstract: Test-time sampling can improve Vision-Language-Action (VLA) policies, but only if the model can efficiently select a good action from multiple candi

applicationsarxiv-cs-cv

TopoPilot: Reliable Conversational Workflow Automation for Topological Data Analysis and Visualization

arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts. Despite this progr

Towards a Systematic Study of Embodied System 2 over Full Task Execution Cycles

model-releasesarxiv-cs-ro

arXiv:2610.17657v1 Announce Type: new Abstract: An embodied brain, or System 2, must turn an abstract goal into actions while discovering relevant scene conditions and checking whether executed skills

Training LLMs for Multi-Agent Collaboration with Verifiable Information Rewards

arXiv:2610.17893v1 Announce Type: cross Abstract: Effective collaboration among large language model (LLM) agents in multi-agent systems requires sharing relevant evidence, requesting missing informat

TSRL: Trigger-based Supervised Reinforcement Learning for Continual Agent Training

arXiv:2610.17726v1 Announce Type: new Abstract: Large language model (LLM) agents excel at complex, multi-step tasks but suffer from catastrophic forgetting during continual learning--acquiring new sk

UEPS: Robust and Efficient MRI Reconstruction

arXiv:2603.18572v2 Announce Type: replace-cross Abstract: Deep unrolled models (DUM) have become the state-of-the-art for accelerated MRI reconstruction, yet their robustness under domain shift remain

Uncertainty-Aware Cortical Surface Reconstruction and Spherical Registration for Heterogeneous Brain MRI

arXiv:2610.16595v1 Announce Type: cross Abstract: Surface-based cortical analysis is useful in many applications as it is a natural way to model the highly folded structure of the cerebral cortex, all

Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

arXiv:2204.09334v4 Announce Type: replace-cross Abstract: Unsupervised domain adaptation approaches have recently succeeded in various medical image segmentation tasks. The reported works often tackle

Who Sets the Pace of Judge Hacking? Judge Capability versus the Policy-Judge Gap

arXiv:2610.15778v1 Announce Type: new Abstract: When a policy is trained with GRPO against a frozen, reference-free LLM judge, the judge accepts more of its answers, but in a post-hoc analysis we dete

A Scalable Learned Iterative Solver for Nonlinear MPC via Temporal Decomposition

arXiv:2610.13480v1 Announce Type: cross Abstract: Nonlinear model predictive control (NMPC) can be applied to large nonlinear systems with complex objectives while enforcing constraints, but the cost

Safety

AutoControl Arena: Synthesizing Executable Test Environments for Frontier AI Risk Evaluation

arXiv:2603.07427v3 Announce Type: replace Abstract: As Large Language Models (LLMs) evolve into autonomous agents, existing safety evaluations face a fundamental trade-off: manual benchmarks are costl

safetyarxiv-cs-ai

BLiMPPI: Benchmark of Linguistic Minimal Pairs for Polarity Items

model-releasesarxiv-cs-cl

arXiv:2610.13607v1 Announce Type: new Abstract: Negative polarity items (NPIs), such as 'anymore' and 'ever', are grammatical only in select environments, predominantly in the context of negation. Bec

Cancerous Backdoor Attack: Gradual Activation via Invisible Tokens and A Stage Controller

arXiv:2610.12644v1 Announce Type: cross Abstract: Backdoor Attacks on Large Language Models (LLMs) typically follow a trigger-response pattern, where satisfying a trigger condition activates a single

researcharxiv-cs-ai

DAG Structure Learning with Node-Varying Heavy-Tailed Disturbances

arXiv:2610.13304v1 Announce Type: new Abstract: DAG structures can be learned from observations by incorporating acyclicity via smooth constraints, such as DAGMA's log-determinant function. Typically,

Data-driven Optimal Sensor Placement for Aerosol Monitoring in the UK

arXiv:2610.12658v1 Announce Type: new Abstract: We develop a data-driven sensor-placement framework and apply it to aerosol monitoring in the United Kingdom (UK). A trained convolutional Gaussian neur

Applications

Discovering Phase Space Structure in Learned Hamiltonian Systems

arXiv:2509.23003v3 Announce Type: replace-cross Abstract: Mechanics-inspired neural dynamical models improve interpretability and physical consistency, but they usually assume a known configuration sp

applicationsarxiv-cs-ai

DuoRate: Two-Rate Per-Expert Precision Allocation for Mixture-of-Experts Serving

arXiv:2610.13328v1 Announce Type: new Abstract: Serving a Mixture-of-Experts (MoE) model pays for expert precision twice: the resident footprint pays for every expert the router can reach, while each

EmbodiedCLBench: Evaluating Continual Learning for Self-Evolving Embodied Agents

model-releasesarxiv-cs-ai

arXiv:2610.13021v1 Announce Type: new Abstract: Continual learning requires models to accumulate past experience and transfer it to new tasks. Despite substantial research on continual learning, exist

Evolving Creatives with Clicks: CTR-Driven Advertising image Editing via Attribute Disentanglement and Preference Alignment

model-releasesarxiv-cs-ai

arXiv:2610.13066v1 Announce Type: cross Abstract: The optimization objective for e-commerce advertising creatives has shifted from aesthetic quality to online business metrics like click-through rate