Search: “models”

Direct Topology Tracking in Continuous Implicit Models

arXiv:2609.12157v1 Announce Type: cross Abstract: We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representa

researcharxiv-cs-lg

14 Sept 2026

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MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models

DGX agent

arXiv:2601.20433v4 Announce Type: replace Abstract: Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling

safetyarxiv-cs-cv

14 Sept 2026

Physics as the label for measuring and correcting materials reasoning in multimodal models

model-releasesarxiv-cs-cv

arXiv:2609.12181v1 Announce Type: new Abstract: Vision-language and language models increasingly interpret materials data, yet benchmarks report that they hallucinate invalid properties and violate ph

14 Sept 2026

Zipbench: Low-Cost Framework for Compressing Comprehensive Benchmarks of Large Language Models

arXiv:2609.12475v1 Announce Type: new Abstract: Comprehensive benchmark suites are essential for improving large language models (LLMs), but many widely used benchmarks are redundant, making evaluatio

14 Sept 2026

Detectable Only Where It Is Confounded: What Verified Duplication Counts Say About Membership Evidence in Language Models

arXiv:2609.10830v1 Announce Type: new Abstract: When a language model finds a sentence unusually cheap to predict, it is tempting to conclude that the sentence was in its training data. Almost every p

OmniHallu: Unified Hallucination Detection for Cross-Modal Comprehension and Generation in Multimodal Large Language Models

arXiv:2609.11244v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse tasks, they suffer from hallucinations where generated o

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

Perturbation: A simple and efficient adversarial tracer for representation learning in language models

arXiv:2603.23821v2 Announce Type: replace Abstract: Linguistic representation learning in deep neural language models (LMs) has been studied for decades, but finding representations in LMs remains an

Audio-Maestro: Enhancing Large Audio-Language Models with Tool-Augmented Reasoning

arXiv:2510.11454v2 Announce Type: replace-cross Abstract: Recent advancements in large multimodal models (LMMs) have shown strong capabilities in audio understanding. However, most systems rely solely

Deep and shallow biases in language models

arXiv:2609.09901v1 Announce Type: new Abstract: Large language models often repeatedly select the same answer even when many alternatives are plausible. Prior work treats this concentration as bias, b

safetyarxiv-cs-cl

Identifying Habit, Physics, and Nuisance in Robot World Models

arXiv:2609.09210v1 Announce Type: cross Abstract: Teleoperated demonstrations are often multimodal even when the underlying dynamics are nearly deterministic given the executed action. We argue that t

researcharxiv-cs-cv

Agents

The Internal Anatomy of Strategic Choice in Large Language Models

arXiv:2609.07478v1 Announce Type: new Abstract: Large language models act as strategic agents and models of human choice, yet choosing like a strategic agent does not mean computing like one. We recor

agentsarxiv-cs-ai

Adapting Vision Foundation Models to Acoustics for Pose-Free 3D Sonar Reconstruction

arXiv:2609.06261v1 Announce Type: new Abstract: Vision foundation models trained on Internet-scale RGB datasets enable remarkable capabilities across a range of tasks, from text-to-video generation to

researcharxiv-cs-cv

Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization

arXiv:2406.04314v4 Announce Type: replace Abstract: Generating visually appealing images is fundamental to modern text-to-image generation models. A potential solution to better aesthetics is direct p

safetyarxiv-cs-cv

BEFORE THE FLIP: Measuring Hidden Score Shifts In Quantized Vision Language Models Before The Answer Changes for Visual Question Answering

model-releasesarxiv-cs-cv

arXiv:2609.06922v1 Announce Type: new Abstract: Quantization makes vision language models (VLMs) cheaper to store and run by using fewer bits to represent their weights. While unchanged answers on vis

Data-driven rational function neural networks: a new method for generating analytical models of rock physics

arXiv:2109.08813v1 Announce Type: cross Abstract: Seismic wave velocity of underground rock plays important role in detecting internal structure of the Earth. Rock physics models have long been the fo

researcharxiv-cs-lg

Discovering Natural Transformation Vulnerabilities in Black-Box Vision Models

arXiv:2609.07110v1 Announce Type: new Abstract: Natural adversarial examples (NAEs) reveal that vision models can fail under realistic semantic changes beyond norm-bounded perturbations. However, gene

researcharxiv-cs-cv

Evaluating Vision-Language Models for Image Quality Assessment using Psychophysical Data

model-releasesarxiv-cs-cv

arXiv:2603.24578v2 Announce Type: replace Abstract: Psychophysical experiments remain the most reliable approach for perceptual image quality assessment (IQA), yet their cost and limited scalability m

A Roadmap for MEG Foundation Models

arXiv:2609.04461v1 Announce Type: cross Abstract: Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific decoding pipelines toward reusable models pr

researcharxiv-cs-ai

A Systematic Evaluation of Cross-Lingual Consistency Enhancement Methods in Multilingual Language Models

arXiv:2609.04409v1 Announce Type: cross Abstract: Multilingual language models often produce inconsistent answers to semantically equivalent questions across languages, motivating methods to improve c

Brain4FMs: A Benchmark of Foundation Models for Electrical Brain Signal

arXiv:2602.11558v2 Announce Type: replace Abstract: Brain foundation models (BFMs) are advancing neurotechnology by learning transferable representations from neural signals, with broad potential in c

Distilled Continuous Diffusion Language Models Can Write Code in Few Steps---or One

arXiv:2609.04531v1 Announce Type: new Abstract: Language generation is almost universally treated as a sequential process: autoregressive models emit one token at a time, while diffusion language mode

researcharxiv-cs-lg

Agents

From Language Models to World-Acting Systems: Progress and Limits of Agentic AI across Digital, Social, Virtual, and Physical Environments

arXiv:2609.04894v1 Announce Type: new Abstract: Large language models become consequential agents when surrounding systems let outputs change external state. Models now call tools, operate interfaces,

agentsarxiv-cs-ai

Knowing When Not to Answer: Pseudo-Ensembles for Abstention in Music Audio-Language Models

arXiv:2609.04362v1 Announce Type: cross Abstract: Music audio-language models are evaluated almost entirely by accuracy on multiple-choice questions. This protocol forces the model to commit to an opt

Multilingual Models for Check-Worthy Social Media Posts Detection

arXiv:2408.06737v2 Announce Type: replace Abstract: This work presents an extensive study of transformer-based NLP models application for detection of social media posts that contain verifiable factua

Investigating the Ability of Large Language Models to Analyze Recipes for Diabetes

arXiv:2609.03967v1 Announce Type: cross Abstract: Several studies have evaluated the ability of Large Language Models (LLMs) for meal planning, yielding positive outcomes. These models can process nat

Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.03225v1 Announce Type: new Abstract: End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through extit{

Representational alignment yields generalizable safety in language models

arXiv:2609.04022v1 Announce Type: cross Abstract: Aligning large language models (LLMs) is essential for their safe deployment. Current alignment methods mainly optimize observable responses, yet mode

Scaling Laws, Tabular Data and Actuarial Ratemaking Models

arXiv:2609.03106v1 Announce Type: new Abstract: Scaling laws in modern deep learning describe how held-out loss improves as model capacity, training data, and compute increase, often following power-l

VoxPrivacy: A Benchmark for Evaluating Interactional Privacy of Speech Language Models

arXiv:2601.19956v2 Announce Type: replace-cross Abstract: As Speech Language Models (SLMs) transition from personal devices to shared, multi-user environments such as smart homes, a new challenge emer

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

arXiv:2609.04061v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful repairs should also be minimal,

Dutch Books for Language Models

arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev

researcharxiv-cs-ai

3 Sept 2026

Applications

General Demographic Pre-trained Models for Enhancing Predictive Performance Across Diseases and Population

arXiv:2509.07330v3 Announce Type: replace-cross Abstract: Foundation models for healthcare require balancing robust generalization across heterogeneous clinical populations and disease settings with t

applicationsarxiv-cs-ai

3 Sept 2026

Language Models Can Control Their Own Attention

arXiv:2609.02737v1 Announce Type: cross Abstract: Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If

3 Sept 2026

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

arXiv:2609.00866v1 Announce Type: cross Abstract: The rapid advancement of vision-language models (VLMs) has accelerated progress in computational pathology; however, whole-slide image (WSI)-based pat

Can Large Language Models Forecast What Researchers Study Next?

arXiv:2609.00747v1 Announce Type: new Abstract: Large language models increasingly generate research ideas, yet judging their novelty or feasibility at generation time does not establish whether they

Consistency Without Alignment: Item-Sensitive Language Models Indistinguishable From Random

arXiv:2609.00576v1 Announce Type: new Abstract: Item-sensitivity, defined as whether a model's choice depends on the specific input rather than on its own output prior, is widely reported as evidence

safetyarxiv-cs-ai

Context Window Failures in Relational Foundation Models

arXiv:2609.00460v1 Announce Type: new Abstract: Recent Relational Deep Learning architectures have been proposed as foundation models for multi-table relational data, yet they impose constrained neigh

Denoising Diffusion Generative Models Secretly Calculate Attentions

arXiv:2609.00885v1 Announce Type: new Abstract: Denoising diffusion models are the dominant architecture for image generation, whereas most natural language generation and modeling are primarily handl

researcharxiv-cs-ai

How Do Language Models Choose Between Context and Memory?

arXiv:2609.00753v1 Announce Type: cross Abstract: When contextual information conflicts with the knowledge stored in model parameters, activation directions can be used to decode and steer which sourc

I-CARE: Analysis of interference-related phenomena in a controllable, diverse and representative unlearning setting for text-to-image models

arXiv:2609.00003v1 Announce Type: new Abstract: Machine unlearning studies the removal of knowledge from an AI model, making the system forget a concept it previously learned. Despite rapid progress i

Lightweight Adaptation of EEG Foundation Models for Stroke Motor Imagery Decoding: Domain Shift and Subject-Level Robustness

arXiv:2609.00282v1 Announce Type: cross Abstract: Motor imagery (MI) electroencephalography (EEG) decoding could support post-stroke rehabilitation, but models developed on healthy cohorts may not tra

Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge

arXiv:2602.17826v2 Announce Type: replace Abstract: Language models exhibit fundamental limitations -- hallucination, brittleness, and lack of formal grounding -- that are particularly problematic in

Patterning in Practice: Debiasing Reward Models with Susceptibilities

arXiv:2609.00699v1 Announce Type: new Abstract: Reward models trained on human preferences are known to suffer from length, formatting, and other stylistic biases. In this paper we use patterning, whi

Revealing Multi-View Hallucination in Large Vision-Language Models

arXiv:2603.23934v2 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) are increasingly being applied to multi-view image inputs captured from diverse viewpoints. Despite this

TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models

arXiv:2609.01277v1 Announce Type: cross Abstract: Although pretrained joint audio-visual diffusion models offer rich control over what to generate, they provide no explicit control over when an uttera

An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models

arXiv:2602.06449v2 Announce Type: replace Abstract: Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requir

safetyarxiv-cs-cl

1 Sept 2026

Applications

Calibrating Small Language Models for Claim Check-Worthiness Detection