arXiv AI

Emergent Latent-State Computation under Stochastic Volatility

arXiv:2607. 25459v1 Announce Type: cross Abstract: Mechanistic interpretability has largely focused on language models and deterministic toy tasks.

arXiv AI

Jul 24

Constrained latent state modeling: A unifying perspective on representation learning under competing constraints

arXiv:2605. 15995v2 Announce Type: replace-cross Abstract: Learning latent representations from complex data is central to modern machine learning, spanning temporal, multimodal, and partially observed systems.

By Gwenol\'e Quellec

multimodal benchmarks

arXiv AI

Jun 2

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting

arXiv:2606. 02138v1 Announce Type: cross Abstract: Out of distribution (OOD) events in multivariate time series forecasting are rare but often dominate real world risk, making average case forecasting insufficient for reliable deployment.

By Xudong Zhang, Jierui Lei, Jiacheng Li, Lingdong Shen, Jian Cui, Haina Tang

benchmarks

arXiv Machine Learning

Jun 3

FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance

arXiv:2606. 03184v1 Announce Type: cross Abstract: Financial forecasting is difficult due to low signal-to-noise ratios, latent factors, heavy tails, regime shifts, and jumps.

By Jiaze Sun, Kelvin J. L. Koa, Ruiyang Ni, Yize Liu, Haonan Chen, Ke-Wei Huang

llms multimodal benchmarks safety

arXiv Machine Learning

Jun 3

State-Coupled Volatility in Latent Dynamical Systems: Recovery Under Partial Observation

arXiv:2606. 02664v1 Announce Type: cross Abstract: Latent state-space models are widely used to study partially observed dynamical systems, yet most formulations assume that process variability is independent of latent-state position.

By Imani Beckett

benchmarks safety

arXiv Machine Learning

Jul 7

Emergence of Nonequilibrium Latent Cycles in Unsupervised Generative Modeling

arXiv:2512. 11415v3 Announce Type: replace-cross Abstract: We show that nonequilibrium dynamics can play a constructive role in unsupervised machine learning by inducing the spontaneous emergence of latent-state cycles.

By Marco Baiesi, Alberto Rosso

diffusion

arXiv AI

Jun 19

How Transparent is DiffusionGemma?

arXiv:2606. 20560v1 Announce Type: cross Abstract: LLM reasoning transparency is a critical affordance for understanding model decisions, mitigating misuse and misalignment, and debugging surprising model behaviors.

By Joshua Engels, Callum McDougall, Bilal Chughtai, Janos Kramar, Senthoran Rajamanoharan, Cindy Wu, Arthur Conmy, Asic Q Chen, Jean Tarbouriech, Min Ma, Brendan O'Donoghue, Jo\~ao Gabriel Lopes de Oliveira, Rohin Shah, Neel Nanda

llms diffusion safety

arXiv Machine Learning

Jul 2

TRIE: An Evaluation Framework for Stochastic PDE Surrogates

arXiv:2607. 00196v1 Announce Type: new Abstract: Many scientific systems exhibit uncertainty from stochastic forcing, unresolved degrees of freedom, or imperfect observations, making reliable surrogate forecasting fundamentally distributional rather than pointwise.

By Bharat Srikishan, Javier E. Santos, Nikhil Muralidhar, Charles D. Young

arXiv Machine Learning

Jun 16

Next-Latent Prediction Transformers Learn Compact World Models

arXiv:2511. 05963v4 Announce Type: replace Abstract: Transformers replace recurrence with a memory that grows with sequence length and self-attention that enables ad-hoc lookups over past tokens.

By Jayden Teoh, Manan Tomar, Kwangjun Ahn, Edward S. Hu, Tim Pearce, Pratyusha Sharma, Akshay Krishnamurthy, Riashat Islam, Alex Lamb, John Langford

llms diffusion benchmarks safety

arXiv AI

Jun 10

One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability

arXiv:2606. 09936v1 Announce Type: cross Abstract: World models are now built on substantially different computational substrates.

By Bhavith Chandra Challagundla, Sanskar Pandey, Param Thakkar, Rishikesh Mallagundla, Yugandhar Reddy Gogireddy, Wenhao Lu, Hindol Roy Choudhury, Shravani Challagundla, Mohamed Deraz Nasr, Spursh Deshpande

llms rag diffusion safety

arXiv Machine Learning

Jun 29

Textual Belief States for World Models: Identifiable Representation Learning Under Strict Mediation

arXiv:2606. 27681v1 Announce Type: new Abstract: World models in partially observed environments rely on latent representations that summarize interaction history, but in many modern LLM-based architectures predictive performance fails to reflect representation quality due to history bypass, rendering the latent state unidentifiable.

By Xiang Gao, Kaiwen Dong, Yuguang Yao, Padmaja Jonnalagedda, Kamalika Das

llms reinforcement-learning

arXiv Machine Learning

Aug 4

Latent-Regime Bias Auditing for Volatility Forecasting

arXiv:2608. 01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that matter for risk management.

By Arthur Chagas, Pedro Bento, Yan Aquino, Arthur Buzelin, Wagner Meira Jr., Cristiano Arbex Valle

safety

arXiv AI

Jul 9

L-GTA: Latent Generative Modeling for Time Series Augmentation

arXiv:2507. 23615v2 Announce Type: replace-cross Abstract: Data augmentation is becoming increasingly important across various areas of time series analysis, including forecasting, classification, and anomaly detection.

By Luis Roque, Vitor Cerqueira, Carlos Soares, Luis Torgo

diffusion benchmarks

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