Search: “models”

Forecast lead time and the timing of crew deployment for weather-driven power outages using AI weather models

arXiv:2610.20918v1 Announce Type: cross Abstract: Utilities request mutual aid crews to restore power after severe storms, and requesting early secures more crews but relies on less accurate forecasts

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Local Ai

Graph Additive Models disentangling feature, topology, and interactions

DGX agent

arXiv:2610.20662v1 Announce Type: cross Abstract: Graph Neural Additive Networks (GNANs) have emerged as effective, interpretable-by-design architectures for graph learning. They achieve transparency

local-aiarxiv-cs-lg

16 Oct 2026

Purify Before You Align: Improving Representation Alignment for Diffusion Models

arXiv:2610.20761v1 Announce Type: new Abstract: Representation alignment improves and accelerates diffusion training by encouraging intermediate features to match a pretrained visual encoder. However,

local-aiarxiv-cs-cv

Hardware

RoleQ: Role-Aligned Scales for Converting Language Models to Ternary

arXiv:2610.21808v1 Announce Type: new Abstract: Weight quantization below four bits shrinks memory and bandwidth at a perplexity that looks acceptable, but often at the cost of factual knowledge and t

hardwarearxiv-cs-ai

VeriVLA: Adaptive Test-Time Verification for Flow-Based VLAs with Latent World Models

arXiv:2610.21985v1 Announce Type: new Abstract: Flow-based Vision-Language-Action (VLA) policies are inherently stochastic: different noise seeds can produce action chunks of varying quality from the

safetyarxiv-cs-ro

Geospatial Vector Geometry as a Native Spatial Modality for Vision-Language Models

arXiv:2610.16769v1 Announce Type: new Abstract: Geospatial reasoning links VLMs to real-world action and decision making. Reliable reasoning requires accurate spatial information and effective spatial

applicationsarxiv-cs-ai

15 Oct 2026

Specification-Guided Synthesis of Deadlock-Free Communication Protocol Refinements with Large Language Models

arXiv:2607.27964v3 Announce Type: replace-cross Abstract: Ensuring behavioural correctness in communication protocols is a central challenge in distributed software systems, as subtle inconsistencies

15 Oct 2026

AlphaRLM: Aligning Language Models for Literature-Grounded Symbolic Factor Discovery

arXiv:2610.14959v1 Announce Type: cross Abstract: Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space. Recent LLM-based

safetyarxiv-cs-lg

Anthropic Executive Says Open-Source AI Models Are Higher Risk

https://www.bloomberg.com/news/articles/2026-10-14/anthropic-executive-says-open-source-ai-models-are-higher-risk https://www.business-standard.com/technology/artificial-intelligence/open-source-ai-mo

local-air-localllama

Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models

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Code-switching (CS), the alternation between languages within an utterance, is common in multilingual speech but underrepresented in pretraining corpora. Increasing CS coverage requires finding releva

Generative Models as Adaptive Trust Regions for Discrete Bayesian Optimisation

arXiv:2610.16992v1 Announce Type: new Abstract: Bayesian optimisation (BO) is a powerful framework for sample-efficient optimisation of expensive black-box functions, but its application to high-dimen

Tutorials

PixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models

arXiv:2601.19060v2 Announce Type: replace Abstract: Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on modula

tutorialsarxiv-cs-cv

Verify, Act, Distill: Turning Test-Time Compute into Test-Time Adaptation for Vision-Language-Action Models

arXiv:2610.14885v1 Announce Type: new Abstract: Test-time compute (TTC), which scores multiple candidate actions at inference time, is a powerful way to improve the execution performance of vision-lan

safetyarxiv-cs-ro

Agents

Infinitesimal Operator World Models: Finite-Sample Guarantees for Offline Reinforcement Learning

arXiv:2511.10383v2 Announce Type: replace-cross Abstract: Continuous-time stochastic processes underlie many natural and engineered systems. In healthcare, autonomous driving, and industrial control,

agentsarxiv-cs-lg

12 Oct 2026

LeapBot-JAC: Joint Action Chains for World Action Models

arXiv:2610.12886v1 Announce Type: new Abstract: Action-chunking policies predict future controls but execute only a prefix before replanning. How should a fixed action-token budget be organized to sup

applicationsarxiv-cs-ro

12 Oct 2026

ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

arXiv:2610.12213v1 Announce Type: cross Abstract: Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Proc

applicationsarxiv-cs-lg

Language Models for Page-Level Layout Decisions in E-commerce Search

arXiv:2610.10920v1 Announce Type: cross Abstract: E-commerce search pages are critical touchpoints for millions of online shoppers. While traditional search engines return a ranked list of results, mo

researcharxiv-cs-cl

Industry

OpenAI revenue falls short, models play hopscotch and Trump cracks down on tech green cards

I’m not going to call the bursting of artificial intelligence bubble yet, not with all that money still pouring into every hardware and software company with AI in their pitch decks. But we got a litt

industrysiliconangle

Agents

Plan-and-Patch: Diffusion Language Models for Agentic Planning

arXiv:2610.10786v1 Announce Type: new Abstract: Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcom

agentsarxiv-cs-ai

PRAXIS: Learning Dynamics of Self-Improving Models with Symbolic Archives

arXiv:2610.11803v1 Announce Type: new Abstract: Self-improving learning systems adapt data selection, optimization, and auxiliary symbolic components, inducing nonstationary objectives outside standar

Tutorials

RISR: Residual-Informed Scientific Equation Discovery with Large Language Models

arXiv:2610.11387v1 Announce Type: cross Abstract: Symbolic regression combines structural search with numerical fitting, but aggregate fit scores do not describe how the remaining error varies across

tutorialsarxiv-cs-ai

AdaPS-LiNGAM: Adaptive Predecessor Selection for Linear Non-Gaussian Acyclic Models under Small-Sample Settings

arXiv:2610.09782v1 Announce Type: new Abstract: Causal discovery becomes particularly challenging when the available sample size is small relative to the number of variables. This challenge also arise

8 Oct 2026

SAREO-FM: Decoupled Semantic Supervision for SAR-EO Foundation Models

arXiv:2610.09317v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) and electro-optical (EO) imagery provide complementary observations: SAR enables day-and-night, weather-resilient sensing

researcharxiv-cs-cv

8 Oct 2026

Second-order optimization of variable projection SVM models and road abnormality detection

arXiv:2610.09617v1 Announce Type: cross Abstract: We introduce a novel second-order optimization framework for minimizing so-called variable projection functionals. We demonstrate that the proposed fr

applicationsarxiv-cs-lg

8 Oct 2026

Evaluation of Active Feature Acquisition Policies with Tabular Foundation Models

arXiv:2610.07406v1 Announce Type: new Abstract: Active feature acquisition learns policies that sequentially acquire features to maximize information about a target variable. We study how to learn and

safetyarxiv-cs-lg

7 Oct 2026

Communication-Efficient Relative Pose Estimation with Vision Foundation Models for Ephemeral Collaborative Perception

arXiv:2607.14539v2 Announce Type: replace Abstract: Relative pose estimation is a fundamental capability for collaborative perception and coordination in multi-robot systems. However, robots encounter

applicationsarxiv-cs-ro

6 Oct 2026

Reward-DAgger: Robot-Gated Interactive Imitation Learning with General-Purpose Progress-Based Reward Models

arXiv:2610.04054v1 Announce Type: new Abstract: Recent advances in robot learning have enabled generalist control policies capable of completing a wide range of tasks. However, their performance degra

safetyarxiv-cs-ro

6 Oct 2026

Contextual Flow Matching: Adaptive Step Selection in Flow Models for Efficient Visual Generation

arXiv:2610.03202v1 Announce Type: cross Abstract: Flow Matching enables high-quality visual generation via continuous-time dynamics, but inference remains costly due to multiple sequential function ev

5 Oct 2026

Reactive Humanoid Multi-Contact Using Learned Stability Models

arXiv:2610.00823v1 Announce Type: new Abstract: We present a planning and control approach to reactively use hand contacts to stabilize a humanoid in low stability scenarios, where only using feet con

researcharxiv-cs-ro

2 Oct 2026

A polynomial time algebraic solution to exact marginal inference in Markov Random Field models

arXiv:1709.09051v3 Announce Type: replace-cross Abstract: This paper develops on algebraic grounds a polynomial time exact linear solution to the hard combinatorial problem of marginal inference in Ma

Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset

arXiv:2609.38213v1 Announce Type: cross Abstract: We introduce a dataset of approximately 10,000 Reynolds-Averaged Navier-Stokes (RANS) simulations of steady, incompressible, two-dimensional subsonic

Audible World Models: Spatially Aware Sound Generation for 3D Worlds

arXiv:2609.38444v1 Announce Type: new Abstract: Text- and image-conditioned world generators can create visually rich 3D environments, yet these worlds often remain silent or rely on soundtracks synth

safetyarxiv-cs-cv

Effects of Structural Allocation of Geometric Task Diversity in Linear Meta-Learning Models

arXiv:2509.18349v4 Announce Type: replace-cross Abstract: Meta-learning aims to leverage information across related tasks to improve prediction on unlabeled data for new tasks when only a small number

Applying Language Models in Clinical Medicine: Recent Trends and Perspectives

arXiv:2609.34780v2 Announce Type: replace Abstract: The use and applicability of artificial intelligence (AI) in medical research and clinical practice has received increasing attention in the literat

safetyarxiv-cs-ai

FairDiff: Mitigating the Self-Reinforcing Matthew Effect in Diffusion Recommender Models

arXiv:2609.36671v1 Announce Type: new Abstract: While the 'Matthew Effect' and filter bubbles are widely recognized outcome-level biases in recommender systems, we reveal that Diffusion Recommender Mo

safetyarxiv-cs-ai

For anyone running local models and still guessing whether a prompt change helped

Running things locally already means you care more about control and reproducibility than most. Worth extending that to your prompts too. There's a live workshop on Oct 3 covering exactly that. Serj S

local-air-ollama

Multichannel Audio Quality Assessment: Extending Pretrained Perceptual Models to Spatial Audio

arXiv:2609.37116v1 Announce Type: cross Abstract: Accurate perceptual quality assessment is essential for evaluating and optimizing spatial audio, where perceived quality depends on both signal fideli

Support-Set Target Leakage in Relational Foundation Models during In-Context Learning: Impact, Detection, and Mitigation

arXiv:2609.36384v1 Announce Type: new Abstract: Relational in-context learning (ICL) conditions predictions on the labeled support examples and their linked tables, creating a failure mode when the su

DF-CBM: Region-Aware Concept Bottleneck Models for Deepfake Detection

arXiv:2609.35096v1 Announce Type: new Abstract: Deepfake detection methods have become increasingly effective yet most provide limited insight into the evidence behind their predictions. However, in f

local-aiarxiv-cs-cv

Tutorials

Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks

arXiv:2602.00449v2 Announce Type: replace-cross Abstract: Latent Chain-of-Thought aims to enable step-by-step computation without emitting long rationales, yet its internal mechanisms remain unclear.

tutorialsarxiv-cs-lg

When Helpful Text Hurts: Option-Redirecting Bias in Vision-Language Models

arXiv:2609.32489v1 Announce Type: cross Abstract: In tri-modal visual question answering (VQA), auxiliary text is commonly used to complement visual and textual inputs, yet its reliability is often un

safetyarxiv-cs-cv

When Known Physics Helps Neural PDE Models: Residual Constraints Out-Regularize Generic Priors for Nonlinear Dynamics

arXiv:2609.34012v1 Announce Type: new Abstract: Neural PDE surrogates increasingly incorporate structural priors, yet it is often unclear whether their gains arise from physics-specific information or

safetyarxiv-cs-lg

Hardware

EAServe: Encode-Aware Disaggregated Serving for Multimodal Large Language Models

arXiv:2609.31551v1 Announce Type: cross Abstract: Disaggregating the two stages, Prefill and Decode, onto separate GPU pools is now a standard optimization for (text-only) LLM serving. However, multim

hardwarearxiv-cs-lg

28 Sept 2026

Fast Plans, Faithful Actions: Closing the Planning-Execution Gap in Hierarchical Vision-Language-Action Models

arXiv:2609.30833v1 Announce Type: new Abstract: Hierarchical vision-language-action (VLA) systems consist of a high-level vision-language planner and a low-level action expert that generates continuou

researcharxiv-cs-ro

28 Sept 2026

Skip the Talk, Re-Focus on Vision: Latent Reasoning for Reasoning Segmentation in Multimodal Large Language Models

arXiv:2609.30783v1 Announce Type: cross Abstract: Reasoning segmentation aims to interpret implicit textual queries and enable fine-grained visual perception, which is critical for applications such a

safetyarxiv-cs-ai

28 Sept 2026

Direction-Scale Decomposition in Action Representation: Rethinking What to Tokenize for Vision-Language-Action Models

arXiv:2609.28865v1 Announce Type: new Abstract: Action representation plays a central role in discrete-token vision-language-action (VLA) learning but remains underexamined. Under conventional pose-in

applicationsarxiv-cs-cv

25 Sept 2026

ICE: Task-Aligned Clifford Latent Fields for Multimodal Graph Foundation Models

arXiv:2609.29398v1 Announce Type: new Abstract: Multimodal attributed graphs connect entities, visual content, language, and observed relations. Learning one foundation across such graphs requires mor

25 Sept 2026

What IDE to use for local models