4 papers
The Complexity of Verifying Feedforward Neural Networks in Quantised Settings
Eric Alsmann, Martin Lange, Marco Sälzer
We investigate the computational complexity of neural network verification in quantised settings. We distinguish three classes of Feedforward Neural Networks (FNNs): rational FNNs…
On the Expressiveness of State Space Models via Temporal Logics
Eric Alsmann, Lowejatan Noori, Martin Lange
We investigate the expressive power of state space models (SSM), which have recently emerged as a potential alternative to transformer architectures in large language models. Build…
The Computational Complexity of Satisfiability in State Space Models
Eric Alsmann, Martin Lange
We analyse the complexity of the satisfiability problem ssmSAT for State Space Models (SSM), which asks whether an input sequence can lead the model to an accepting configuration.…
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
We analyse the complexity of the satisfiability problem, or similarly feasibility problem, (trSAT) for transformer encoders (TE), which naturally occurs in formal verification or i…