Search: “models”

Graded Entity-Familiarity Readouts in Language Models: Polish Adaptation, Cross-Language Robustness, and Refusal Steering

arXiv:2607.13568v1 Announce Type: cross Abstract: Can a language model estimate its familiarity with an entity before generating an answer? We study activations at the final prompt token in twelve ins

16 Jul 2026

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Model Releases

S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving

DGX agent

arXiv:2607.13926v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable potential for high-level reasoning in autonomous driving, yet they fundamentally struggle to

model-releasesarxiv-cs-ro

16 Jul 2026

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

arXiv:2607.13395v1 Announce Type: new Abstract: The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from t

researcharxiv-cs-lg

16 Jul 2026

Belief-reality separation lives in routing over a shared value slot in language models

model-releasesarxiv-cs-cl

arXiv:2607.11945v1 Announce Type: new Abstract: Capable language models hold what a character believes apart from what is true: told 'Anna believes the cup is blue; in reality it is red,' they answer

So Many Opinions, So Many LLMs: Comparing Large Language Models to Traditional Machine Learning for Open- Ended Survey Analysis

arXiv:2607.11890v1 Announce Type: cross Abstract: Open-ended surveys offer valuable insights, but they are notoriously difficult to analyze at scale. Building on previous work that employed traditiona

Verifier-Based Reinforcement Fine-Tuning of Reasoning Models for Thermal Energy Storage Control

arXiv:2607.12856v1 Announce Type: new Abstract: Buildings are expected to shift cooling loads in response to grid conditions. Thermal energy storage (TES) enables this shift, but scheduling it well re

VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression

arXiv:2607.12756v1 Announce Type: new Abstract: Vision-language models (VLMs) process large numbers of visual tokens, resulting in substantial inference latency and memory overhead. This has motivated

InfraQR: Edge-Placed QR-Inspired Structured Patch Attacks on Infrared Vision-Language Models

arXiv:2607.07288v1 Announce Type: new Abstract: Infrared vision-language models are increasingly used for perception under low-light and adverse visual conditions, yet their robustness to localized st

9 Jul 2026

Multi-Agent Robotic Control with Onboard Vision-Language Models

model-releasesarxiv-cs-ro

arXiv:2607.07403v1 Announce Type: cross Abstract: Vision Language Models (VLMs) and Vision Language Action (VLA) models have shown promise in robotic control. Yet, they face significant challenges reg

9 Jul 2026

Safety

ELBO-T2IAlign: A Generic ELBO-Based Method for Calibrating Pixel-level Text-Image Alignment in Diffusion Models

arXiv:2506.09740v2 Announce Type: replace-cross Abstract: Diffusion models excel at image generation. Recent studies have shown that these models not only generate high-quality images but also encode

safetyarxiv-cs-ai

Prior Bias in Vision Language Models on UML Diagram Interpretation

arXiv:2607.02853v1 Announce Type: new Abstract: Vision Language Models (VLMs) are increasingly applied to software engineering artifacts, especially UML class diagrams whose meaning depends on visual

Punching Above Their Weight: Classification-Head Fine-Tuning of Tiny Language Models (TLMs) for Verifiable Multiple-Choice Tasks

arXiv:2607.03801v1 Announce Type: cross Abstract: We define Tiny Language Models (TLMs) as models below roughly 3B parameters that fit on mainstream consumer devices. We study how to adapt them for an

SPEARBench: A Benchmark for Naturalness Evaluation in Streaming Speech-to-Speech Language Models

arXiv:2607.05365v1 Announce Type: cross Abstract: Streaming speech-to-speech language models aim to answer spoken queries directly with synthetic speech. However, standard speech and text benchmarks d

SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments

arXiv:2607.05264v1 Announce Type: new Abstract: Existing video benchmarks evaluate action recognition on consumer videos, egocentric recordings, or simulated industrial environments. They do not test

The Good, the Bad, and the Brittle: Benchmarking Robustness and Generalisation of Histopathology Foundation Models

arXiv:2607.04401v1 Announce Type: new Abstract: How robust and generalisable are pathology foundation models and have their scaling limites been reached? We benchmarked twelve pathology foundation mod

They Infer What You Meant: Models Represent Communicative Intent More Reliably Than They Act On It

arXiv:2607.03598v1 Announce Type: cross Abstract: When a person shares something with a language model, the model often answers the surface of the message rather than what the sender was doing by send

Safety

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models

arXiv:2509.25533v2 Announce Type: replace-cross Abstract: As Vision Language Models (VLMs) are deployed across safety-critical applications, understanding and controlling their behavioral patterns has

safetyarxiv-cs-ai

VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

arXiv:2407.11691v5 Announce Type: replace Abstract: We present VLMEvalKit: an open-source toolkit for evaluating large multi-modality models based on PyTorch. The toolkit aims to provide a user-friend

When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters

arXiv:2607.04919v1 Announce Type: new Abstract: Deploying a time series foundation model requires GPU infrastructure, engineering overhead, and carries no guarantee of improvement over XGBoost. We pro

From Lab to Reality: A Practical Evaluation of Deep Learning Models and LLMs for Vulnerability Detection

arXiv:2512.10485v2 Announce Type: replace-cross Abstract: Vulnerability detection methods based on deep learning (DL) have shown strong performance on benchmark datasets, yet their real-world effectiv

3 Jul 2026

mupscaling small models: Principled warm starts and hyperparameter transfer

arXiv:2602.10545v2 Announce Type: replace-cross Abstract: Modern large-scale neural networks are often trained and released in multiple sizes to accommodate diverse inference budgets. To improve effic

3 Jul 2026

Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge

arXiv:2607.01829v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for aviation business operations, from documentation and training generation to customer facing a

3 Jul 2026

Tutorials

Self-conditioned Flow Map Language Models via Fixed-point Flows

arXiv:2607.00714v1 Announce Type: cross Abstract: Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditi

tutorialsarxiv-cs-ai

2 Jul 2026

An Empirical Study of Security Calibration in Large Language Models for Code

arXiv:2606.31159v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly transforming software development, yet their use in security-critical contexts raises a key question: do mode

Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models

arXiv:2606.31630v1 Announce Type: new Abstract: Language models increasingly write probabilistic programs (in NumPyro, Stan, or Pyro), but a program that compiles, runs, and passes every unit test can

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

arXiv:2508.09156v3 Announce Type: replace-cross Abstract: We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientifi

TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios

arXiv:2603.29759v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have accelerated their application to indoor safety hazards assessment. However, existing ben

A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models

arXiv:2606.28757v1 Announce Type: new Abstract: Generative world models hold immense promise as scalable simulators for autonomous systems, particularly for synthesizing rare but safety-critical multi

Benchmarking Geospatial Foundation Models for Agriculture Applications

arXiv:2606.29664v1 Announce Type: new Abstract: Geospatial foundation models pretrained on satellite imagery promise broad generalization across remote sensing tasks and regions, but their geographic

Compressed Sensing for Capability Localization in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2603.03335v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit a wide range of capabilities, including mathematical reasoning, code generation, and linguistic behaviors. We s

Agents

Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems

arXiv:2504.02918v3 Announce Type: replace Abstract: Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, p

agentsarxiv-cs-cv

Flow Reasoning Models: Scaling Reasoning Through Iterative Self-Refinement

arXiv:2606.29150v1 Announce Type: new Abstract: Discrete flow models have recently shown promising performance on few-step text generation; however, when naively applied to structured reasoning tasks

Kriging and neural network models for pressure losses across perforated plates

arXiv:2606.29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates

researcharxiv-cs-lg

Obliviate: Erasing Concepts from Autoregressive Image Generation Models

arXiv:2606.28643v1 Announce Type: new Abstract: The widespread adoption of generative AI models has intensified concerns about misuse, including the creation of unsafe or disturbing imagery. To mitiga

Hardware

SSM Meets Video Diffusion Models: Efficient Long-Term Video Generation with Structured State Spaces

arXiv:2403.07711v5 Announce Type: replace-cross Abstract: Given the remarkable achievements in image generation through diffusion models, the research community has shown increasing interest in extend

hardwarearxiv-cs-ai

Structural Certification for Reliable Physical Design with Language Models

arXiv:2606.30107v1 Announce Type: new Abstract: An unreliable language model can be made to produce reliable physical designs if the authority to assert is moved out of the model: the model proposes,

From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond

arXiv:2606.28127v1 Announce Type: cross Abstract: The AI community has framed the relationship between large language models (LLMs) and world models as a dichotomy: LLMs predict tokens; world models s

29 Jun 2026

HybridCodec: Modeling Discrete and Continuous Representations for Efficient Speech Language Models

arXiv:2606.27627v1 Announce Type: cross Abstract: Discrete audio representations have become increasingly popular for building multimodal text-audio systems and integrating audio capabilities into Lar

29 Jun 2026

Do Image Editing Models Understand Lighting?

arXiv:2606.26738v1 Announce Type: new Abstract: While recent advancements in generative image editing models have achieved stunning visual fidelity, it remains an open question whether these systems p

26 Jun 2026

Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation

arXiv:2606.26984v1 Announce Type: new Abstract: Unified multimodal models capable of both understanding and generation have achieved remarkable strides. However, despite their unified designs, existin

26 Jun 2026

Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach

arXiv:2602.22188v2 Announce Type: replace Abstract: Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of

researcharxiv-cs-lg

25 Jun 2026

Uncertainty Quantification for Computer-Use Agents: A Benchmark across Vision-Language Models and GUI Grounding Datasets

model-releasesarxiv-cs-cl

arXiv:2606.25760v1 Announce Type: cross Abstract: Computer-use agents turn vision-language model (VLM) predictions into executable GUI clicks, so reliable uncertainty estimates are essential for rejec

25 Jun 2026

BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases

arXiv:2606.24883v1 Announce Type: new Abstract: Artificial intelligence (AI) has achieved remarkable success in medical imaging, but it is widely recognized that these models often perform inconsisten

24 Jun 2026

Lightweight Transformer Models for On-Device Fault Detection: A Benchmark Study on Resource-Constrained Deployment

arXiv:2606.24173v1 Announce Type: cross Abstract: On-device fault detection enables real-time diagnostics without cloud dependency, but deploying machine learning models on resource-constrained hardwa

24 Jun 2026

Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.23147v1 Announce Type: new Abstract: We propose Assistron, a shared autonomy model that leverages Vision-Language-Action (VLA) models to assist the user in daily activities. Our approach is

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

arXiv:2606.22188v1 Announce Type: new Abstract: Large multi-modal language models are increasingly deployed in high-stakes domains, making well-calibrated uncertainty essential. Traditional Bayesian m

Applications

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation

arXiv:2606.21413v1 Announce Type: cross Abstract: Nowadays, large multilingual translation models demonstrate impressive translation capabilities in the machine translation benchmarks. This raises a p

applicationsarxiv-cs-lg

Tutorials

Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently

arXiv:2606.22938v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated that reinforcement fine-tuning of pretrained base models can lead to significant gains

tutorialsarxiv-cs-lg