Search: “models”

FLY-EVAL++: An Evidence-Driven Evaluation Protocol for Safety-Constrained Flight Prediction with Large Language Models

arXiv:2609.04021v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in safety-critical, physics-governed environments requires more than accuracy-based metrics, because predictions

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Safety

How Perturbations Propagate: A Multi-Level Analysis of Robustness in Large Language Models

DGX agent

arXiv:2609.03322v1 Announce Type: new Abstract: Language models encounter typos, corrupted text, altered words, and disrupted token order, yet robustness is usually evaluated only through output behav

safetyarxiv-cs-cl

4 Sept 2026

Industry

Introducing Z1T: Our first family of transformer-like models made for sparse probabilistic hardware like Z1 Achieving up to 140x energy effi…

Introducing Z1T: Our first family of transformer-like models made for sparse probabilistic hardware like Z1 Achieving up to 140x energy efficiency gains over GPUs and revealing a new scaling law for s

industryemad-mostaque--x

Applications

LLM4CKD: Large Language Models for Early Stage Chronic Kidney Disease Screening

arXiv:2609.04013v1 Announce Type: new Abstract: Early screening of chronic kidney disease (CKD) is critical for timely intervention, yet most machine learning (ML) and deep learning (DL) approaches re

applicationsarxiv-cs-ai

R2S-Eval: Robot Evaluation with Real-to-Sim Calibration via Vision-Language Models

arXiv:2609.03276v1 Announce Type: new Abstract: Evaluating robot manipulation policies is becoming increasingly important as generalist models, particularly vision-language-action (VLA) models, are de

safetyarxiv-cs-ro

SafeRI: Recognition and Intervention for Token-Level Safety Intervention in Large Vision Language Models

arXiv:2609.03544v1 Announce Type: new Abstract: Existing safety alignment methods for vision-language models usually modify the model behavior globally: once the safety parameters are trained or loade

safetyarxiv-cs-cv

Agents

Semantic Bayesian World Models

arXiv:2609.03834v1 Announce Type: new Abstract: Knowledge graphs describe reality in crisp assertions, while the systems now consuming them, foundation models and autonomous agents, reason natively in

agentsarxiv-cs-ai

A Study of Conditional Diffusion Models for Open-Loop Control under Dry Friction and Stiction

model-releasesarxiv-cs-lg

arXiv:2609.01756v1 Announce Type: new Abstract: Diffusion models have recently emerged as expressive generative priors for planning and control. This paper studies Action Diffusion, an action-sequence

Tutorials

Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

arXiv:2609.02766v1 Announce Type: new Abstract: Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical

tutorialsarxiv-cs-lg

Frontier models sabotaging local AI implementations?

For a few days I've been working on creating a custom local-only harness for some work related research using Codex / GPT 5.6 Sol and the model feels not only dumber than usual, but straight up counte

local-air-localllama

InfraPatch: Cross-Task Targeted Grayscale Patch Attacks on Infrared-Adapted Vision-Language Models

arXiv:2609.02233v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) have emerged as a promising paradigm for multimodal perception under low-visibility conditions, yet their ro

local-aiarxiv-cs-ai

Morphology signal in whole slide image foundation models can automatically triage slides

model-releasesarxiv-cs-cv

arXiv:2609.01987v1 Announce Type: new Abstract: Patient exams in the cancer diagnosis and staging process typically generate several whole slide images (WSIs). One of the initial steps in training mod

PIVOTSBench: Evaluating Fine-Grained Interpersonal Relationship Reasoning in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.23092v2 Announce Type: replace Abstract: Humans possess an innate ability to understand fine-grained interpersonal relationships, which is central to everyday social interactions. Although

Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

arXiv:2609.02108v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to the auto-regressive paradigm. With bidirectional attention and any-order g

SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models

arXiv:2609.02886v1 Announce Type: new Abstract: We introduce SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference. Training

Transfer Safety Awareness for Cross-Modal Safety Drift in Multimodal Large Language Models

arXiv:2609.02082v1 Announce Type: cross Abstract: Visual modality enhances the capabilities of multimodal large language models (MLLMs) but also introduces a safety concern: a benign textual query may

A Cone-Constrained Bilinear Decomposition for Total Scaled-Gradient Variation Models

model-releasesarxiv-cs-cv

arXiv:2609.00036v1 Announce Type: new Abstract: The total scaled-gradient variation (TSGV) regularizer, derived from sparse modeling of piecewise-linear structures, has been shown to preserve edges an

ASSERT: Adaptive Stochastic Sampling for Robust Diffusion Models on Analog Compute-in-Memory Hardware

arXiv:2609.00955v1 Announce Type: new Abstract: Diffusion models achieve strong image generation quality but incur high iterative denoising costs. Analog compute-in-memory (CIM) can accelerate matrix-

safetyarxiv-cs-cv

Automatic Item Generation for Personality Situational Judgment Tests with Large Language Models

model-releasesarxiv-cs-ai

arXiv:2412.12144v5 Announce Type: replace-cross Abstract: Personality assessment through situational judgment tests (SJTs) offers unique advantages over traditional Likert-type self-report scales, yet

Capability-Gated Language Models: Security Composes, Utility Does Not

arXiv:2609.00445v1 Announce Type: cross Abstract: Deployed language model safeguards (safety fine-tuning, filtering, unlearning) vary by principal only outside the model weights: filters are reconfigu

IntroConformal: Conformal Factuality Guarantees for Large Vision-Language Models via Introspective Signals

arXiv:2609.01375v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved strong multimodal performance, yet ensuring the factual correctness of generated content remains ch

researcharxiv-cs-cl

Applications

Medical Causal Hypothesis Verification with Large Language Models

arXiv:2609.00063v1 Announce Type: cross Abstract: The growing use of large language models (LLMs) for search and information retrieval underscores the need to evaluate their reliability in high-stakes

applicationsarxiv-cs-ai

S^2Prune: Spatially Structured Visual Token Pruning for Multimodal Large Language Models

arXiv:2609.01224v1 Announce Type: new Abstract: Visual token pruning reduces the inference overhead of multimodal large language models (MLLMs) by retaining only a subset of visual tokens. Existing me

local-aiarxiv-cs-cv

SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue

model-releasesarxiv-cs-cl

arXiv:2609.01548v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in advice seeking and decision making that may affect social judgements. Despite stigma's profound ef

Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2609.01279v1 Announce Type: cross Abstract: Emotion is expressed in text along a wide spectrum, from surface lexical cues to inferences entangled with content. Most layer-wise analyses of emotio

Validity-Aware Jailbreak Evaluation for Large Language Models

arXiv:2609.00498v1 Announce Type: new Abstract: Jailbreak robustness has become central to large language model (LLM) safety evaluation, yet prevailing methodologies rely primarily on refusal behavior

VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferences

model-releasesarxiv-cs-ai

arXiv:2609.00921v1 Announce Type: new Abstract: Personalized Large Language Models (PLLMs) aim to tailor responses to individual users, where a central challenge is preference reasoning: inferring que

Tutorials

What, Where, and How: Probing Spatiotemporal Representations in Video Foundation Models

arXiv:2609.01551v1 Announce Type: new Abstract: Self-supervised video foundation models learn rich spatiotemporal representations, yet it remains unclear what visual concepts these representations enc

tutorialsarxiv-cs-cv

DART: Draft-Agreement Routing for Training-Free Adaptive Thinking Budgets in Hybrid Reasoning Models

arXiv:2606.23181v2 Announce Type: replace Abstract: Hybrid reasoning models can answer directly or spend extra tokens on extended thinking. A practical router should choose between these modes for eac

FLM: Frequency-Aware Language Models for Generative Image Compression

arXiv:2608.28687v1 Announce Type: new Abstract: Generative models have significantly improved the performance ceiling of image lossy compression at low bitrates by exploiting learned priors. However,

Flow-JEPA: Flow Matching for Robust Latent Dynamics in JEPA World Models

arXiv:2608.29029v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) have shown strong potential for learning compact predictive representations, and LeWorldModel (LeWM)

From Speech to Subtitles: Evaluating ASR Models in Subtitling Italian Television Programs

model-releasesarxiv-cs-cl

arXiv:2512.19161v2 Announce Type: replace Abstract: Subtitles are essential for video accessibility and audience engagement. Modern Automatic Speech Recognition (ASR) systems, built upon Encoder-Decod

Hearing the Order: Investigating Position Bias in Large Audio-Language Models

arXiv:2510.00628v3 Announce Type: replace-cross Abstract: Large audio-language models (LALMs) are often used in tasks that involve reasoning over ordered options. An open question is whether their pre

Information-Based Calibration of Uncertainty Quantification in Product-of-Experts Gaussian Process Models

arXiv:2608.29349v1 Announce Type: new Abstract: Gaussian process (GP) regression with a single global GP (GP-glo) incurs cubic computational cost, limiting scalability to large datasets. Product-of-ex

local-aiarxiv-cs-lg

Learning to Restore More: Continual Capability Expansion for Pretrained Image Restoration Models

arXiv:2608.30305v1 Announce Type: new Abstract: Image restoration models are typically trained with a fixed set of capabilities. When new restoration requirements emerge, existing solutions usually tr

MMPCBench: Benchmarking Multimodal Large Language Models on Proactive Critique of Flawed Inputs

arXiv:2608.29286v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) evolve into sophisticated interactive assistants, their reliability depends not only on following instructio

MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models

arXiv:2603.02482v2 Announce Type: replace-cross Abstract: Safety evaluation of multimodal large language models requires tracking not only whether an attack succeeds, but also how the interaction unfo

When Does Predictor-Based RL Align with Human Perception? A Study of Subjective Rewards in Codec-Based Speech Language Models

arXiv:2608.31035v1 Announce Type: new Abstract: Codec-based text-to-speech (TTS) models make language-model post-training applicable to speech generation, but it remains unclear when learned perceptua

Applications

Conditional Diffusion Models for Energy-Efficient Driving

arXiv:2608.28142v1 Announce Type: new Abstract: Electrification of commercial delivery fleets is shifting fleet routing from distance- and time-based optimization toward energy-aware decision-making.

applicationsarxiv-cs-lg

31 Aug 2026

Timing-Aware Repurchase Prediction for Web-Scale E-Commerce: Survival Models for Multi-Surface Grocery Recommendation

model-releasesarxiv-cs-lg

arXiv:2608.28393v1 Announce Type: cross Abstract: Repurchase recommenders in e-commerce are commonly framed as a binary question asking 'will this customer buy this item within W days', a formulation

31 Aug 2026

Visual Token Coding for Video Multimodal Large Language Models

arXiv:2608.28008v1 Announce Type: new Abstract: In this paper, we propose a new token compression paradigm for video Multimodal Large Language Models (MLLMs), termed Visual Token Coding (VTC). Inspire

31 Aug 2026

Artificial Intelligence Models Can Predict and Collaboratively Modulate Human Memory Search

arXiv:2608.26152v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many langu

Is Your Neighborhood Safe? Place-based Stigma in Large Language Models' Urban Safety Judgments

arXiv:2608.26188v1 Announce Type: new Abstract: Large language models are increasingly used to inform safety decisions in cities, such as where it is safe to walk, rent, or travel. We ask whether such

Large Models for Battery Prognostics and Health Management: A Review and Future Roadmap

arXiv:2608.26111v1 Announce Type: new Abstract: Battery Prognostics and Health Management (BPHM) is critical for ensuring the safe, reliable, and cost-effective operation of batteries across electric

local-aiarxiv-cs-ai

Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models

arXiv:2608.27259v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly pe

safetyarxiv-cs-lg

Surgical Video Generation From Diffusion to World Models: A Survey

arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio

safetyarxiv-cs-cv

Adversarial Training of Linear Models under Stealthy Attacks

arXiv:2608.25681v1 Announce Type: new Abstract: Predictive models are widely used in many fields, but are vulnerable to false data injection attacks. To address this, detection schemes and adversarial

researcharxiv-cs-lg

27 Aug 2026

Demystifying Reinforcement Learning Post-Training of Language Models

arXiv:2608.24949v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training has emerged as a powerful framework for enhancing the capabilities of large language models (LLMs), enabling