This paper studies the benefits and limitations of feedback in computation, specifically in the context of deterministic programs with random clock movements.

The authors provide a deterministic algorithm for solving integer programs in standard form with improved running time.

KoAT is a tool that automatically infers complexity bounds and proves termination of integer programs using an alternating modular analysis approach and a portfolio of techniques.

This paper measures the lower bound for the shortest program generating a sequence, proving a conservation law and providing a deterministic engine to recover generating programs for certain sequences…

The paper proves that platform-deterministic inference is a necessary and sufficient condition for trustworthy AI, establishing that AI trust fundamentally relies on consistent arithmetic.

The paper introduces Grid Programs, a novel, Turing-complete model of computation where programs are two-dimensional arrangements of instructions, fundamentally departing from linear code structures.

This paper proposes a method for verifying functional correctness of message-passing concurrent programs using Constrained Horn Clause (CHC) solving.

The paper introduces Post-Deterministic Distributed Systems (PDDS) as a new model to coordinate autonomous infrastructure where participants, including stochastic agents, produce divergent reasoning p…

This paper introduces symbolic SOS, a rule format for specifying both concrete and symbolic operational semantics of programming languages.

This paper improves max-policy iteration by replacing mathematical optimization with value iteration and proposes min-policy iteration as an alternative to linear programming.

The Euclidean shortest vector problem is deterministically NP-hard to approximate within any constant factor for arbitrary constants.

The paper develops typed extended decision diagrams (TEDDs) to improve the scalability of deductive probabilistic program verification.

This paper provides a counterexample to a claimed linear-time comparison-based algorithm for solving deterministic graphical games (DGGs) and gives a deterministic linear-time reduction from the direc…

This paper proves that a strongly consistent solution to the Causal Observability Problem is unachievable at the observable boundary and explores the impact of instrumentation placement on monitor gua…

This paper introduces a probabilistic language for programming large language model-based flows to quantify and propagate uncertainty.

This paper introduces InvWeaver, a neuro-symbolic framework for synthesizing loop invariants in programs with multiple interacting loops.