Cover Image

PAC learning PDFA from data streams

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Baumgartner, Robert, Verwer, Sicco
Format:	Preprint
Published:	2026
Subjects:	Formal Languages and Automata Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PDFA Distillation via String Probability Queries
by: Baumgartner, Robert, et al.
Published: (2024)

Database-assisted automata learning
by: Walinga, Hielke, et al.
Published: (2024)

Analyzing constrained LLM through PDFA-learning
by: Carrasco, Matías, et al.
Published: (2024)

Algebra and coalgebra of stream products
by: Boreale, Michele, et al.
Published: (2021)

Learning Reward Machines from Partially Observed Policies
by: Shehab, Mohamad Louai, et al.
Published: (2025)

Learning Deterministic Finite-State Machines from the Prefixes of a Single String is NP-Complete
by: Dumitru, Radu Cosmin, et al.
Published: (2026)

Finite Sentence-Interface Control for Learning Bounded-Fan-Out Linear MCFGs under Fixed Monoid Typing
by: Kuriyama, Takayuki
Published: (2026)

SMT-Based Active Learning of Weighted Automata
by: Ferreira, Tiago, et al.
Published: (2026)

Continuous Diffusion Models Can Obey Formal Syntax
by: Kim, Jinwoo, et al.
Published: (2026)

Unsupervised Hierarchical Skill Discovery
by: Harvey, Damion, et al.
Published: (2026)

Solomonoff induction
by: Sterkenburg, Tom F.
Published: (2026)

Warm Starting State-Space Models with Automata Learning
by: Fishell, William, et al.
Published: (2026)

Extending AALpy with Passive Learning: A Generalized State-Merging Approach
by: von Berg, Benjamin, et al.
Published: (2025)

Deconstructing Subset Construction -- Reducing While Determinizing
by: Nicol, John, et al.
Published: (2025)

Transformers as Transducers
by: Strobl, Lena, et al.
Published: (2024)

Stochastic Alignments: Matching an Observed Trace to Stochastic Process Models
by: Li, Tian, et al.
Published: (2025)

A Constructive Framework for Nondeterministic Automata via Time-Shared, Depth-Unrolled Feedforward Networks
by: Dhayalkar, Sahil Rajesh
Published: (2025)

Active Learning of Symbolic Automata Over Rational Numbers
by: Hagedorn, Sebastian, et al.
Published: (2025)

Learning Weighted Finite Automata over the Max-Plus Semiring and its Termination
by: Okudono, Takamasa, et al.
Published: (2024)

Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
by: Chen, Boqi, et al.
Published: (2024)

A Detailed Account of Compositional Automata Learning through Alphabet Refinement
by: Henry, Leo, et al.
Published: (2025)

Partial Answer of How Transformers Learn Automata
by: Zhang, Tiantian
Published: (2025)

Sampling from Your Language Model One Byte at a Time
by: Hayase, Jonathan, et al.
Published: (2025)

TR2MTL: LLM based framework for Metric Temporal Logic Formalization of Traffic Rules
by: Manas, Kumar, et al.
Published: (2024)

An Algebraic View of the Expressivity of Recurrent Language Models
by: Nowak, Franz, et al.
Published: (2026)

Bifocal Attention: Harmonizing Geometric and Spectral Positional Embeddings for Algorithmic Generalization
by: Awadhiya, Kanishk
Published: (2026)

Simulating Hard Attention Using Soft Attention
by: Yang, Andy, et al.
Published: (2024)

The Expressive Capacity of State Space Models: A Formal Language Perspective
by: Sarrof, Yash, et al.
Published: (2024)

Language Models over Canonical Byte-Pair Encodings
by: Vieira, Tim, et al.
Published: (2025)

From Formal Language Theory to Statistical Learning: Finite Observability of Subregular Languages
by: Hayashi, Katsuhiko, et al.
Published: (2025)

DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products
by: Siems, Julien, et al.
Published: (2025)

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues
by: Grazzi, Riccardo, et al.
Published: (2024)

Unraveling Syntax: How Language Models Learn Context-Free Grammars
by: Schulz, Laura Ying, et al.
Published: (2025)

Comparison of different Unique hard attention transformer models by the formal languages they can recognize
by: Ryvkin, Leonid
Published: (2025)

Constructing a BPE Tokenization DFA
by: Berglund, Martin, et al.
Published: (2024)

Correct and Optimal: the Regular Expression Inference Challenge
by: Valizadeh, Mojtaba, et al.
Published: (2023)

The Counting Power of Transformers
by: Sälzer, Marco, et al.
Published: (2025)

MLRegTest: A Benchmark for the Machine Learning of Regular Languages
by: van der Poel, Sam, et al.
Published: (2023)

Completely reachable automata: a quadratic decision algorithm and a quadratic upper bound on the reaching threshold
by: Ferens, Robert, et al.
Published: (2022)

Learning Formal Specifications from Membership and Preference Queries
by: Shah, Ameesh, et al.
Published: (2023)