Search: “models”

arXiv:2609.17306v1 Announce Type: cross Abstract: Multi-agent Systems (MAS) combine multiple model outputs to solve complex reasoning tasks. However, despite rapid growth of available open-source mode

agentsarxiv-cs-ai

16 Sept 2026

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Hardware

HoliBench: A Cross-Platform Benchmarking and Deployment Toolkit for Foundation Models in CPS-IoT Applications

DGX agent

arXiv:2609.12412v1 Announce Type: cross Abstract: Foundation models, including large language models, vision-language models, and time-series foundation models, are increasingly deployed on embedded a

hardwarearxiv-cs-lg

14 Sept 2026

Logit Refiner: Improving Visual Autoregressive Models via Intra-Scale Dependency Modeling

model-releasesarxiv-cs-cv

arXiv:2609.11804v1 Announce Type: new Abstract: Visual Autoregressive Models (VAR) generate images through next-scale prediction, producing all tokens within each scale in parallel. We show that this

11 Sept 2026

SVI2LoD3: Agent-Driven Reconstruction of LoD3 Facade Openings in Semantic 3D City Models from Volunteered Street View Imagery using Large Language and Visual Models

model-releasesarxiv-cs-cv

arXiv:2608.29992v1 Announce Type: new Abstract: This paper presents an end-to-end, agent-driven pipeline for the LoD3 reconstruction of facade openings in 3D city models, producing directly usable Cit

Bridge Graphical Models: Coupling, Projection, and Current-Preserving Dynamics for Generative Modeling

arXiv:2608.19144v1 Announce Type: new Abstract: Continuous-time generative models are often built from endpoint-conditioned bridges, but generation requires a different object: a non-anticipative Mark

researcharxiv-cs-lg

20 Aug 2026

An Omitted Mode Is a Rare Rule: The Sampling-Verification Danger Law in Continuous Code World Models

arXiv:2608.17956v1 Announce Type: cross Abstract: In the Code World Model paradigm an LLM synthesizes an executable world model that a classical planner searches, and the model is accepted when it rep

19 Aug 2026

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models

arXiv:2607.27421v1 Announce Type: new Abstract: Intent classification is a core component of task-oriented dialogue systems, yet practitioners have limited systematic guidance for selecting deployable

31 Jul 2026

Learning by Surprise: Adaptive Mitigation of Model Collapse in Large Language Models

arXiv:2410.12341v4 Announce Type: replace-cross Abstract: As AI-generated content increasingly populates the web, generative AI models are at growing risk of being trained on their own outputs, a proc

researcharxiv-cs-ai

1 Jul 2026

TDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling

arXiv:2606.31268v1 Announce Type: cross Abstract: The growing demand for privacy-preserving data sharing has positioned synthetic data generation as a critical component of responsible AI workflows. D

safetyarxiv-cs-ai

1 Jul 2026

Local Ai

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models

arXiv:2506.20771v2 Announce Type: replace Abstract: We propose a latent score-based generative AI framework for learning stochastic, non-local closure models and constitutive laws in nonlinear dynamic

local-aiarxiv-cs-lg

30 Jun 2026

Local Ai

Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models

arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod

local-aiarxiv-cs-ai

26 Jun 2026

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation

arXiv:2606.05290v1 Announce Type: new Abstract: Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring ret

safetyarxiv-cs-cv

5 Jun 2026

The Variance Brain Foundation Models Forgot: Third-Order Statistics Predict Cognition Where Billion-Parameter Models Fail

arXiv:2606.04010v1 Announce Type: cross Abstract: Brain foundation models (BFMs) are self-supervised Transformers pretrained on fMRI data. We posit that these models should capture each subject's cogn

4 Jun 2026

Are vision-language models ready to zero-shot replace supervised classification models in agriculture?

model-releasesarxiv-cs-cv

arXiv:2512.15977v3 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose solutions for visual recognition tasks, yet their reliability for agricul

12 May 2026

ModelLens: Finding the Best for Your Task from Myriads of Models

arXiv:2605.07075v1 Announce Type: new Abstract: The open-source model ecosystem now contains hundreds of thousands of pretrained models, yet picking the best model for a new dataset is increasingly in

11 May 2026

Tutorials

Rethinking the Need for Source Models: Source-Free Domain Adaptation from Scratch Guided by a Vision-Language Model

arXiv:2605.02604v1 Announce Type: new Abstract: Source-Free Domain Adaptation (SFDA) adapts source models to target domains without accessing source data, addressing privacy and transmission issues. H

tutorialsarxiv-cs-cv

5 May 2026

Can Large Language Models Implement Agent-Based Models? An ODD-based Replication Study

arXiv:2602.10140v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can now synthesize non-trivial executable code from textual descriptions, raising an important question: can LLMs

1 May 2026

Learning Physics from Pretrained Video Models: A Multimodal Continuous and Sequential World Interaction Models for Robotic Manipulation

arXiv:2603.00110v2 Announce Type: replace Abstract: The scarcity of large-scale robotic data has motivated the repurposing of foundation models from other modalities for policy learning. In this work,

safetyarxiv-cs-ro

24 Apr 2026

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training

arXiv:2604.20012v1 Announce Type: cross Abstract: Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from

safetyarxiv-cs-ai

23 Apr 2026

Robust Reward Modeling for Large Language Models via Causal Decomposition

arXiv:2604.13833v1 Announce Type: new Abstract: Reward models are central to aligning large language models, yet they often overfit to spurious cues such as response length and overly agreeable tone.

16 Apr 2026

Tutorials

Selecting Feature Interactions for Generalized Additive Models by Distilling Foundation Models

arXiv:2604.13332v1 Announce Type: new Abstract: Identifying meaningful feature interactions is a central challenge in building accurate and interpretable models for tabular data. Generalized additive

tutorialsarxiv-cs-lg

16 Apr 2026

Learning World Models for Interactive Video Generation

arXiv:2505.21996v3 Announce Type: replace-cross Abstract: Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. Ho

14 Apr 2026

Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models

arXiv:2604.02340v2 Announce Type: replace-cross Abstract: Recent advances in masked diffusion language models (MDLMs) narrow the quality gap to autoregressive LMs, but their sampling remains expensive

researcharxiv-cs-cl

14 Apr 2026

Sentiment Classification of Gaza War Headlines: A Comparative Analysis of Large Language Models and Arabic Fine-Tuned BERT Models

arXiv:2604.08566v1 Announce Type: new Abstract: This study examines how different artificial intelligence architectures interpret sentiment in conflict-related media discourse, using the 2023 Gaza War

13 Apr 2026

Sensor-Language-Action Models

arXiv:2610.08244v1 Announce Type: new Abstract: Sensors are useful not only for understanding the world but also for deciding what to do next. Existing sensor models however largely stop at perception

7 Oct 2026

HyperWorld: Hypergraph-Structured State Serialization Improves Learned Textual World Models

arXiv:2609.00002v1 Announce Type: new Abstract: World models enable language-model agents to predict environment dynamics and plan before acting. In text environments, the model must learn symbolic ac

safetyarxiv-cs-ai

2 Sept 2026

Autoregressive Mosaics: Probing 2D Spatial Reasoning in Text-Only Language Models

arXiv:2608.30751v1 Announce Type: new Abstract: Large language models (LLMs) trained only on text and code can sometimes generate programs that draw recognizable images. However, it is unclear whether

Learning Action Models with Conditional and Quantified Effects via Uncertainty-Guided Exploration

arXiv:2608.30955v1 Announce Type: new Abstract: Accurate action models are critical for effective planning. Existing action-model learning methods largely assume simple action representations or becom

A tale of perfect fit and phantom optima: how data-driven models can fail in real-time optimization

arXiv:2608.23885v1 Announce Type: cross Abstract: Real-time optimization (RTO) relies on process models to locate economically optimal operating conditions. Because developing first-principles models

26 Aug 2026

Causal Analysis for Time Series Foundation Models

arXiv:2608.24303v1 Announce Type: new Abstract: Transitioning from bespoke time series models towards time series foundation models changes the relationship of model and application from one-to-one to

safetyarxiv-cs-lg

26 Aug 2026

Open-Weight Masked Introspection: Measuring What Language Models Can Report About Their Own Computation

arXiv:2608.20569v1 Announce Type: new Abstract: Are frontier models able to introspect about their internal states? Recent work suggests that under certain conditions a complex enough model can audit

researcharxiv-cs-ai

24 Aug 2026

Toward Reusability of AI Models Using Dynamic Updates of AI Documentation

arXiv:2604.17626v1 Announce Type: cross Abstract: This work addresses the challenge of disseminating reusable artificial intelligence (AI) models accompanied by AI documentation (a.k.a., AI model card

21 Apr 2026

Modeling Time-Dependent Responses of Optical Compressors with Selective State Space Models

arXiv:2408.12549v4 Announce Type: replace-cross Abstract: This paper presents a method for modeling optical dynamic range compressors using deep neural networks with Selective State Space models. The

researcharxiv-cs-ai

7 Oct 2026

World Properties without World Models: Distributional Associations and the Interpretation of Decoding Results from Language Models

arXiv:2603.04317v2 Announce Type: replace-cross Abstract: A growing literature shows that variables can be linearly decoded from the activations of large language models (LLMs). These range from prope

7 Oct 2026

ReFract: Benchmarking Perspective Awareness in Language Model Agents with Text World Models

arXiv:2610.03356v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in high-stakes settings such as industrial maintenance and equipment fault troubleshooting,

5 Oct 2026

Time Series Foundation Models for Process Model Forecasting

arXiv:2512.07624v2 Announce Type: replace Abstract: Process Model Forecasting (PMF) aims to predict how the control-flow structure of a process evolves over time by modeling the temporal dynamics of d

researcharxiv-cs-lg

22 Sept 2026

Optimal Model Activation Policies for Inference Networks of Large Language Models

arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost

16 Sept 2026

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

arXiv:2609.11838v1 Announce Type: new Abstract: Cardiovascular screening models trained on national health surveys routinely report areas under the receiver operating characteristic curve (AUROC) near

11 Sept 2026

Model Selection and Parameter Estimation for Multidimensional Gaussian Mixture Models with a Common Covariance Matrix

arXiv:2603.19657v2 Announce Type: replace-cross Abstract: We study model-order selection and component-mean estimation for multidimensional Gaussian mixture models with a known common covariance matri

Model Selection and Parameter Estimation of One-Dimensional Gaussian Mixture Models

arXiv:2404.12613v4 Announce Type: replace-cross Abstract: In this paper, we study the problem of learning one-dimensional Gaussian mixture models (GMMs) with a specific focus on estimating both the mo

Leveraging Large Language Models for Systematic Literature Review of Disease Spread Models

arXiv:2608.26150v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have created new opportunities to streamline and potentially automate many research processes, inclu

28 Aug 2026

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges

arXiv:2607.28636v1 Announce Type: new Abstract: LLMs increasingly serve as automated judges, but their judgments remain vulnerable to cognitive biases. Existing mitigations mostly rely on prompt-drive

3 Aug 2026

Knowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language Modeling

arXiv:2607.12831v1 Announce Type: new Abstract: Language models encode substantial factual knowledge in their parameters, which can lead to unreliable behavior when this knowledge is outdated, incompl

researcharxiv-cs-cl

15 Jul 2026

Resample or Reroute? Budget-Aware Test-Time Model Selection for Large Language Models

arXiv:2607.08665v1 Announce Type: new Abstract: Routing among large language models (LLMs) trades response quality against serving cost, motivated by the reported gap between deployed routers and a pe

10 Jul 2026

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo

7 Jul 2026

AutoTrainess: Teaching Language Models to Improve Language Models Autonomously

arXiv:2606.31551v1 Announce Type: new Abstract: Training language models (LMs) remains a highly human-intensive process, even as frontier language model agents become increasingly capable at software

1 Jul 2026

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models

arXiv:2606.25086v1 Announce Type: new Abstract: Many modern Language Model (LM) pipelines return an averaged model, such as an exponential moving average of the training iterates, rather than the fina

25 Jun 2026

Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling

arXiv:2606.24650v1 Announce Type: new Abstract: We present Harmonic, a hierarchical state space model (SSM) for language modeling. The architecture stacks three recurrent levels at progressively slowe