Extracting Finite Automata from RNNs Using State Merging

28 January 2022

Papers citing "Extracting Finite Automata from RNNs Using State Merging"

12 / 12 papers shown

Title
DeepDFA: Automata Learning through Neural Probabilistic Relaxations Elena Umili Roberto Capobianco AI4CE 23 1 0 16 Aug 2024
On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning Franz Nowak Anej Svete Alexandra Butoi Ryan Cotterell ReLM LRM 54 13 0 20 Jun 2024
What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages Nadav Borenstein Anej Svete R. Chan Josef Valvoda Franz Nowak Isabelle Augenstein Eleanor Chodroff Ryan Cotterell 42 12 0 06 Jun 2024
Lower Bounds on the Expressivity of Recurrent Neural Language Models Anej Svete Franz Nowak Anisha Mohamed Sahabdeen Ryan Cotterell 39 0 0 29 May 2024
Transformers Can Represent $n$ -gram Language Models Anej Svete Ryan Cotterell 37 17 0 23 Apr 2024
Simulating Weighted Automata over Sequences and Trees with Transformers Michael Rizvi M. Lizaire Clara Lacroce Guillaume Rabusseau AI4CE 53 0 0 12 Mar 2024
On Efficiently Representing Regular Languages as RNNs Anej Svete R. Chan Ryan Cotterell 36 1 0 24 Feb 2024
Interpretability Illusions in the Generalization of Simplified Models Dan Friedman Andrew Kyle Lampinen Lucas Dixon Danqi Chen Asma Ghandeharioun 19 14 0 06 Dec 2023
LUNA: A Model-Based Universal Analysis Framework for Large Language Models Da Song Xuan Xie Jiayang Song Derui Zhu Yuheng Huang Felix Juefei Xu Lei Ma ALM 35 3 0 22 Oct 2023
Recurrent Neural Language Models as Probabilistic Finite-state Automata Anej Svete Ryan Cotterell 32 2 0 08 Oct 2023
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth Edi Muškardin Martin Tappler Ingo Pill B. Aichernig Thomas Pock 6 0 0 29 Jun 2023
Grokking phase transitions in learning local rules with gradient descent Bojan Žunkovič E. Ilievski 63 16 0 26 Oct 2022