Search: “models”

Cross-Model Consistency of Feature Importance in Electrospinning: Separating Robust from Model-Dependent Features

model-releasesarxiv-cs-lg

arXiv:2605.04905v1 Announce Type: new Abstract: Electrospinning is a highly sensitive fabrication process in which small variations in operating parameters can significantly influence fiber morphology

7 May 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models

DGX agent

arXiv:2602.04509v4 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on task-specific data is an effective way to improve performance on downstream applications. Ho

model-releasesarxiv-cs-cl

5 May 2026

On Solomonoff Induction in Large Language Models and the Limits of Self-Improving: The Singularity Is Not Near Without Symbolic Model Synthesis

arXiv:2601.05280v3 Announce Type: replace-cross Abstract: On the one hand, the question of whether large language models (LLMs) are Solomonoff induction estimators has become an explicit question at t

12 Aug 2026

Agents

What Iterated Self-Feeding Probes of Language Models Measure, and a test that separates the construction from the model

arXiv:2608.10986v1 Announce Type: new Abstract: A growing class of methods probes a language model by feeding it its own output: self-consistency, iterated refinement, agentic loops. We ask what such

agentsarxiv-cs-cl

12 Aug 2026

Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models

arXiv:2608.09696v1 Announce Type: new Abstract: Predicting the answer to interventional ``what if'' questions --- the outcome of an action never taken --- requires a mechanistic, causal model, not a c

11 Aug 2026

Beyond Foundation Models: Dimension-Aware Neural Architecture Search with Small-Data Representation Models for Cryocooler Lifetime Prediction

arXiv:2608.06993v1 Announce Type: cross Abstract: Large-scale pretrained time-series models achieve strong results through large-scale pretraining and task-agnostic representation learning, but they r

10 Aug 2026

Transformers Struggle to Use Their Emergent World Models: Revisiting the Tower of Hanoi, and the Illusion of Thinking

arXiv:2608.07077v1 Announce Type: new Abstract: The Tower of Hanoi is a simple planning puzzle that in prior work has proven challenging for large reasoning models (LRMs). Current models solve the sta

10 Aug 2026

Cross-Architecture Steering Transfer in Language Models: A Systematic Empirical Study

arXiv:2608.05164v1 Announce Type: new Abstract: Independently trained large language models may develop shared internal representations of semantic concepts despite architectural differences -- but wh

7 Aug 2026

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling

arXiv:2608.02602v1 Announce Type: new Abstract: Language remains an outlier in generative modeling: while images, video, and audio are increasingly modeled in continuous latent spaces, text generation

4 Aug 2026

BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi

arXiv:2607.23344v1 Announce Type: new Abstract: Named Entity Recognition (NER) for low-resource languages such as Marathi remains a challenging task due to limited annotated resources and linguistic c

28 Jul 2026

Evaluating and Understanding Model Editing for Medical Vision Language Models

arXiv:2607.05310v1 Announce Type: new Abstract: Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining. Howe

7 Jul 2026

Research

Rethinking Foundation Model Collaboration: Enhancing Specialized Models through Proxy Task Reasoning

arXiv:2606.31157v1 Announce Type: new Abstract: Foundation models are increasingly integrated into embodied intelligence systems, but directly assigning them structured prediction tasks requires preci

researcharxiv-cs-cv

1 Jul 2026

A Benchmark of State-Space Models vs. Transformers and BiLSTM-based Models for Historical Newspaper OCR

arXiv:2604.00725v2 Announce Type: replace Abstract: End-to-end OCR for historical newspapers remains challenging, as models must handle long text sequences, degraded print quality, and complex layouts

24 Jun 2026

Epidemiology of Model Collapse: Modeling Synthetic Data Contamination via Bilayer SIR Dynamics

arXiv:2606.05168v1 Announce Type: new Abstract: Training on synthetic data causes model collapse, but existing analyses treat this as single-chain degradation. In reality, the AI ecosystem involves cr

5 Jun 2026

Agents

Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models

arXiv:2606.02914v1 Announce Type: new Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remai

agentsarxiv-cs-ai

3 Jun 2026

Distilling Game Code World Model Generation into Lightweight Large Language Models

arXiv:2605.24375v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown great ability in generating executable code from natural language, opening the possibility of automatically cons

26 May 2026

Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models

arXiv:2605.07872v1 Announce Type: cross Abstract: Multimodal reward models have advanced substantially in text and image domains, yet progress in video understanding reward modeling remains severely l

11 May 2026

Agents

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling

arXiv:2605.00412v1 Announce Type: cross Abstract: World models have recently re-emerged as a central paradigm for embodied intelligence, robotics, autonomous driving, and model-based reinforcement lea

agentsarxiv-cs-ro

4 May 2026

Exploring the Limits of Pruning: Task-Specific Neurons, Model Collapse, and Recovery in Task-Specific Large Language Models

arXiv:2604.27115v1 Announce Type: new Abstract: Neuron pruning is widely used to reduce the computational cost and parameter footprint of large language models, yet it remains unclear whether neurons

1 May 2026

Applications

A Nationwide Japanese Medical Claims Foundation Model: Balancing Model Scaling and Task-Specific Computational Efficiency

arXiv:2604.22348v1 Announce Type: new Abstract: Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising app

applicationsarxiv-cs-lg

27 Apr 2026

Modeling Multi-Dimensional Cognitive States in Large Language Models under Cognitive Crowding

arXiv:2604.17174v1 Announce Type: new Abstract: Modeling human cognitive states is essential for advanced artificial intelligence. Existing Large Language Models (LLMs) mainly address isolated tasks s

21 Apr 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

Modeling Memory-Dependent Reliability of LLMs: A Hidden Markov Model

arXiv:2607.22951v1 Announce Type: cross Abstract: Reliability assessment of large language models (LLMs) seeks to estimate the probability that a model produces correct responses under a specified ope

28 Jul 2026

Research

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

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving

arXiv:2606.29879v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) provide powerful semantic understanding and commonsense reasoning for End-to-End Autonomous Driving (E2E-AD) planning. H

30 Jun 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

Unifying Model-Free Efficiency and Model-Based Representations via Latent Dynamics

arXiv:2602.12643v2 Announce Type: replace-cross Abstract: We present Unified Latent Dynamics (ULD), a novel reinforcement learning algorithm that unifies the efficiency of model-free methods with the

4 Jun 2026

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

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

model-releasesarxiv-cs-lg

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

The Partial Testimony of Logs: Evaluation of Language Model Generation under Confounded Model Choice

arXiv:2605.01311v1 Announce Type: new Abstract: Offline evaluation of language models from usage logs is biased when model choice is confounded: the same user-side factors that influence which model i

safetyarxiv-cs-lg

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

SMSI: System Model Security Inference: Automated Threat Modeling for Cyber-Physical Systems

arXiv:2604.23905v1 Announce Type: cross Abstract: Threat modeling for cyber-physical systems (CPS) remains a largely manual exercise. This project presents SMSI (System Model Security Inference), a hy

28 Apr 2026

Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!

arXiv:2507.03014v2 Announce Type: replace-cross Abstract: Large language models (LLMs) face significant copyright and intellectual property challenges as the cost of training increases and model reuse

27 Apr 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

Deliberative Alignment is Deep, but Uncertainty Remains: Inference time safety improvement in reasoning via attribution of unsafe behavior to base model

arXiv:2604.09665v1 Announce Type: cross Abstract: While the wide adoption of refusal training in large language models (LLMs) has showcased improvements in model safety, recent works have highlighted

safetyarxiv-cs-ai

14 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

Research

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

Forgetting-Resistant and Lesion-Aware Source-Free Domain Adaptive Fundus Image Analysis with Vision-Language Model

arXiv:2602.19471v2 Announce Type: replace Abstract: Source-free domain adaptation (SFDA) aims to adapt a model trained in the source domain to perform well in the target domain, with only unlabeled ta

11 Aug 2026

Rethinking Expert Training for Model Merging with Prompt Learning

arXiv:2607.24465v1 Announce Type: new Abstract: Model merging aims to combine multiple domain-specialized experts trained from a shared foundation model into a single multi-task model. Existing approa