Search: “models”

CinematicVQA: Benchmarking Film-Grammar Reasoning in Large Vision-Language Models

arXiv:2609.28813v1 Announce Type: new Abstract: Cinematography, the craft of visual storytelling through framing, lighting, and camera operation, fundamentally shapes how audiences perceive and emotio

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Safety

Combining Evasive and Braking Reactions for Safety Reference Models in Automated Vehicles

DGX agent

arXiv:2609.29738v1 Announce Type: new Abstract: Computational models of careful and competent human drivers are essential for scenario-based evaluation of automated driving systems (ADS). However, mos

safetyarxiv-cs-ro

25 Sept 2026

Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

arXiv:2609.29194v1 Announce Type: cross Abstract: Mobile robots require robust, real-time fault detection capable of continuous adaptation on constrained edge hardware. While deep time-series models e

QINA: Quantum-Inspired Nonlinear Adapters for Pretrained Vision Models

arXiv:2609.29592v1 Announce Type: cross Abstract: Adapting large pretrained vision models under limited data and frozen-backbone constraints remains a central challenge in transfer learning. While lig

The Alignment Illusion in Multimodal Large Language Models

arXiv:2609.30210v1 Announce Type: new Abstract: Layer-wise visual-text similarity in Multimodal Large Language Models (MLLMs) is widely interpreted as evidence that the language model progressively in

safetyarxiv-cs-cv

UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasound

arXiv:2609.28610v1 Announce Type: new Abstract: Benchmarking is an increasingly critical part of research in machine learning and the domains where it is applied, including healthcare. Yet, despite th

Causal Tracing of Audio-Text Fusion in Large Audio Language Models

arXiv:2603.13768v2 Announce Type: replace-cross Abstract: Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features

Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection

arXiv:2609.26860v1 Announce Type: cross Abstract: Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewa

CoRe-WAM: Correspondence-Aligned Temporal Residuals for World Action Models

arXiv:2609.27314v1 Announce Type: new Abstract: Comparing current and past observations helps robots understand scene changes and select subsequent actions during manipulation. However, comparing visu

Enhancing Small Language Models for Power Outage Report Generation via Minimum Risk Training

arXiv:2609.27197v1 Announce Type: new Abstract: Minimum Risk Training (MRT) enables neural machine translation models to directly optimize sequence-level evaluation metrics instead of relying only on

researcharxiv-cs-ai

Neither Silence nor Overlap Is Failure: Intent-Conditioned Evaluation of Turn-Taking in Full-Duplex Spoken Dialogue Models

arXiv:2609.27372v1 Announce Type: cross Abstract: Benchmarks for full-duplex spoken dialogue models score turn-taking with binary fixed-window rules that reward immediate response or silence by comple

What Do Tabular Foundation Models Compute In Context? In-Situ Representation Refinement through Attention-Gated Updates

arXiv:2609.27679v1 Announce Type: new Abstract: What reusable computation should a tabular foundation model learn when every table defines a new supervised task? We develop in-situ representation refi

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

arXiv:2609.27603v1 Announce Type: cross Abstract: In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: t

From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models

arXiv:2609.24084v1 Announce Type: cross Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification dif

researcharxiv-cs-ai

Agents

GameDirector: Decoupling Gameplay Logic from Rendering for Player-Configurable Game World Models

arXiv:2609.25652v1 Announce Type: new Abstract: Recent game world models support realistic visual simulation and interactive gameplay based on player inputs. However, they typically learn environment

agentsarxiv-cs-cv

IndustrialVLA-Bench: A Traceable Multi-Axis Evaluation of Open Robot Policy Models

arXiv:2609.25562v1 Announce Type: new Abstract: Open robot policies increasingly follow two paradigms: vision-language-action models (VLAs) directly map observations and instructions to actions, where

One-Step Generative Surrogate Models via Block-Triangular Joint Drifting

arXiv:2609.26435v1 Announce Type: new Abstract: Drifting provides a direct route to one-step generative models, but applying it directly to stochastic transition modeling requires multiple samples of

researcharxiv-cs-lg

RGSQ: Riemannian Geometry-Sensitive Quantization for Large Vision-Language Models

arXiv:2609.25492v1 Announce Type: new Abstract: Large vision-language models (VLMs) can be efficiently deployed under stringent memory and latency constraints through post training quantization (PTQ).

researcharxiv-cs-cv

Vision-Language Models as copilots for Autonomous UAV Navigation: Analysis of Latency and Reliability in Degraded Environments

arXiv:2609.26084v1 Announce Type: new Abstract: The integration of Vision-Language Models (VLMs) in autonomous Unmanned Aerial Vehicles (UAVs) offers unprecedented semantic reasoning capabilities. How

VLAQuantBench: Closed-Loop Evaluation of Post-Training Quantization for Vision-Language-Action Models

arXiv:2609.25376v1 Announce Type: new Abstract: Post-training quantization reduces the memory requirements of vision-language-action (VLA) models, but precision selection must account for the interact

An Efficient and Effective Watermarking Scheme for the Protection of the Intellectual Property Rights of Video Generative Models

arXiv:2609.23586v1 Announce Type: new Abstract: The rapid development of video generative models (VGMs) has enabled the generation of highly realistic synthetic videos, raising concerns about the inte

researcharxiv-cs-cv

BadWAM: When World-Action Models Dream Right but Act Wrong

arXiv:2607.15207v2 Announce Type: replace Abstract: World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representat

safetyarxiv-cs-lg

ConsistWorld: Evidence Routing for Consistent Multi-Agent World Models

arXiv:2609.22641v1 Announce Type: new Abstract: Autoregressive video world models enable temporally coherent generation for a single observer. Extending them to multiple agents requires consistency ac

Dissecting Hierarchical Reasoning Models: A Mechanistic Study

arXiv:2609.22197v1 Announce Type: new Abstract: We study Hierarchical Reasoning Model (HRM), a representative hierarchical Transformer-based latent reasoning model with many variants, on Sudoku, Maze,

researcharxiv-cs-lg

Dissecting Training-Free Uncertainty Estimation in Multimodal Large Language Models

arXiv:2609.22206v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of multimodal tasks, yet understanding and quantifying

Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions

arXiv:2609.23703v1 Announce Type: new Abstract: Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated

researcharxiv-cs-cl

Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning

arXiv:2601.06787v2 Announce Type: replace Abstract: Large Language Models (LLMs) are known to contain significant redundancy, yet a systematic explanation for why certain components, particularly in h

Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models

arXiv:2609.24879v1 Announce Type: new Abstract: Counterfactual image generation answers questions about how a subject would have looked under retrospective, hypothetical scenarios. Recent methods have

Logits are All We Need to Adapt Closed Models

arXiv:2502.06806v5 Announce Type: replace-cross Abstract: Many commercial Large Language Models (LLMs) are often closed-source, limiting developers to prompt tuning for aligning content generation wit

researcharxiv-cs-cl

Applications

MechaTerp-TRACE: A Novel Approach for Component Ablation Analysis in Language Models

arXiv:2609.22163v1 Announce Type: new Abstract: Interpretability research on large language models has produced accounts of factual recall in feed-forward layers and of token relationships in self-att

applicationsarxiv-cs-cl

Tutorials

NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models

arXiv:2609.24313v1 Announce Type: new Abstract: World models aim to capture environmental dynamics and predict future trajectories, showing growing potential for embodied intelligence. Physics-informe

tutorialsarxiv-cs-cv

Rethinking Class Imbalance for Single-Cell Foundation Models: A Systematic Benchmark Across Architectures and Long-Tail Loss Functions

arXiv:2609.23325v1 Announce Type: new Abstract: Single-cell foundation models (scGPT, scBERT, Geneformer) achieve cell-type classification accuracy up to 97.5% in our experiments, yet this aggregate a

WaveFront Decoding: Parallelized Self-Speculative Decoding for Looped Language Models

arXiv:2609.23033v1 Announce Type: new Abstract: Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequen

What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior

arXiv:2609.24576v1 Announce Type: cross Abstract: Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While thi

safetyarxiv-cs-cv

Tutorials

What Matters in Designing World Action Models: An Empirical Study

arXiv:2609.24048v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing wor

tutorialsarxiv-cs-ro

Local Ai

Adapting Rigid-Body Dynamics Derivatives for Constraint Embedding Closed-Chain Models

arXiv:2609.21024v1 Announce Type: new Abstract: This paper extends an existing algorithm for the first-order derivatives of rigid-body dynamics to the case of closed-chain kinematic systems modeled us

local-aiarxiv-cs-ro

Local Ai

Assessment of Machine Learning-Based Critical Heat Flux Models in the CTF Subchannel Code for Square Rod Bundle Prediction

arXiv:2609.21995v1 Announce Type: new Abstract: The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direc

local-aiarxiv-cs-lg

CESBench: Benchmarking Large Language Models on Cryptographic Engineering Security for IoT Devices

arXiv:2609.21344v1 Announce Type: cross Abstract: For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical access can attack the implementation directly,

Local Ai

Cultural Alignment in Large Language Models Using Soft Prompt Tuning

arXiv:2503.16094v2 Announce Type: replace Abstract: Large Language Model (LLM) alignment is commonly achieved through supervised fine-tuning or reinforcement learning, both of which require labeled or

local-aiarxiv-cs-cl

Do Quantum Models Scale Like LLMs?

arXiv:2609.20912v1 Announce Type: new Abstract: In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered

PRIME: Perception Feedback with Situational Memory Embeddings in VLA Models

arXiv:2609.22040v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models for autonomous driving operate primarily through feedforward inference across the perception--reasoning--pla

Towards Secure Cloud-Native Computing: Unveiling Kubernetes Misconfigurations with Large Language Models

arXiv:2609.20834v1 Announce Type: new Abstract: In the rapidly evolving landscape of cloud-native computing, Organizations are increasingly adopting infrastructure models that emphasize scalability, f

A Unified Evaluation Framework for Trustworthy Large Language Models, Agentic AI, and Multimodal Systems

arXiv:2609.19524v1 Announce Type: new Abstract: Benchmark scores alone provide an incomplete basis for assessing the trustworthiness of modern artificial intelligence systems. Large language models (L

AVTrace: Diagnosing Audio-Visual Temporal Reasoning in Omni Models

arXiv:2609.19991v1 Announce Type: cross Abstract: Omni models can describe video content, but can they locate events in time, preserve event order, and judge audio-visual synchronization? We introduce

Fine-Tuning Models for Biomedical Relation Extraction

arXiv:2609.20169v1 Announce Type: new Abstract: Next-Generation Sequencing has revolutionized the study of genetic mutations, enabling large-scale investigations into their roles in disease developmen

Tutorials

JEPA-Anything: Learning Predictive Models across Different Worlds

arXiv:2609.20800v1 Announce Type: new Abstract: World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-spe

tutorialsarxiv-cs-cl

Applications

LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

arXiv:2509.03405v2 Announce Type: replace Abstract: Language models (LMs) increasingly drive real-world applications that require world knowledge. However, the internal processes through which models

applicationsarxiv-cs-cl

{M}^2Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models