Cover Image

Verification of the Implicit World Model in a Generative Model via Adversarial Sequences

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Balogh, András, Jelasity, Márk
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How not to Stitch Representations to Measure Similarity: Task Loss Matching versus Direct Matching
by: Balogh, András, et al.
Published: (2024)

When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models
by: Guo, Zhixiang, et al.
Published: (2026)

No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
by: Szász, Attila, et al.
Published: (2025)

Masked Generative Priors Improve World Models Sequence Modelling Capabilities
by: Meo, Cristian, et al.
Published: (2024)

World Model Robustness via Surprise Recognition
by: Zollicoffer, Geigh, et al.
Published: (2025)

Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models
by: Ziani, Abdelhakim, et al.
Published: (2026)

Implicit Language Models are RNNs: Balancing Parallelization and Expressivity
by: Schöne, Mark, et al.
Published: (2025)

Generative Adversarial Model-Based Optimization via Source Critic Regularization
by: Yao, Michael S., et al.
Published: (2024)

Training Implicit Generative Models via an Invariant Statistical Loss
by: de Frutos, José Manuel, et al.
Published: (2024)

Probabilistic ML Verification via Weighted Model Integration
by: Morettin, Paolo, et al.
Published: (2024)

Scalable Energy-Based Models via Adversarial Training: Unifying Discrimination and Generation
by: Yin, Xuwang, et al.
Published: (2025)

On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
by: Peng, Ze, et al.
Published: (2025)

The Extrapolation Power of Implicit Models
by: Decugis, Juliette, et al.
Published: (2024)

Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
by: Huang, Jianhao, et al.
Published: (2026)

GenPlan: Generative Sequence Models as Adaptive Planners
by: Karthikeyan, Akash, et al.
Published: (2024)

Design Principles for Sequence Models via Coefficient Dynamics
by: Sieber, Jerome, et al.
Published: (2025)

Do Neurons Dream of Primitive Operators? Wake-Sleep Compression Rediscovers Schank's Event Semantics
by: Balogh, Peter
Published: (2026)

The Anxiety of Influence: Bloom Filters in Transformer Attention Heads
by: Balogh, Peter
Published: (2026)

Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modeling
by: Zhao, Chenran, et al.
Published: (2026)

Discrete World Models via Regularization
by: Bizzaro, Davide, et al.
Published: (2026)

Exploring the Landscape for Generative Sequence Models for Specialized Data Synthesis
by: Zbeeb, Mohammad, et al.
Published: (2024)

Context-Former: Stitching via Latent Conditioned Sequence Modeling
by: Zhang, Ziqi, et al.
Published: (2024)

Adversarial Environment Design via Regret-Guided Diffusion Models
by: Chung, Hojun, et al.
Published: (2024)

Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generation
by: Tang, Haocheng, et al.
Published: (2025)

Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer
by: Liu, Zhihan, et al.
Published: (2024)

Implicit Neural Differential Model for Spatiotemporal Dynamics
by: Akhare, Deepak, et al.
Published: (2025)

Towards Unraveling and Improving Generalization in World Models
by: Fang, Qiaoyi, et al.
Published: (2024)

A Hybrid Model for Traffic Incident Detection based on Generative Adversarial Networks and Transformer Model
by: Lu, Xinying, et al.
Published: (2024)

Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
by: Xu, Jiawei, et al.
Published: (2024)

IGN : Implicit Generative Networks
by: Luo, Haozheng, et al.
Published: (2022)

SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
by: Cundy, Chris, et al.
Published: (2023)

InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement
by: Cheng, Mingyue, et al.
Published: (2026)

Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
by: Li, Kenneth, et al.
Published: (2022)

Rethinking the Intermediate Features in Adversarial Attacks: Misleading Robotic Models via Adversarial Distillation
by: Zhao, Ke, et al.
Published: (2024)

The Geometry of Self-Verification in a Task-Specific Reasoning Model
by: Lee, Andrew, et al.
Published: (2025)

RewriteNets: End-to-End Trainable String-Rewriting for Generative Sequence Modeling
by: Vejendla, Harshil
Published: (2026)

Implicit Maximum Likelihood Estimation for Real-time Generative Model Predictive Control
by: Lee, Grayson, et al.
Published: (2026)

Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
by: Mereu, Riccardo, et al.
Published: (2025)

GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
by: Li, Zaitang, et al.
Published: (2023)

In-Context Reinforcement Learning via Communicative World Models
by: Martinez-Lopez, Fernando, et al.
Published: (2025)