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This is the full version of a paper submitted to the Computability in Europe (CiE 2023) conference, with all proofs omitted there. In 2012 P. D. Azar and S. Micali introduced a new model of interactive proofs, called "Rational Interactive…

Computational Complexity · Computer Science 2023-05-09 Daniil Musatov , Georgii Potapov

Logic programming with tabling and constraints (TCLP, tabled constraint logic programming) has been shown to be more expressive and in some cases more efficient than LP, CLP or LP + tabling. Previous designs of TCLP systems did not fully…

Programming Languages · Computer Science 2018-09-18 Joaquín Arias , Manuel Carro

This paper investigates the powers and limitations of quantum entanglement in the context of cooperative games of incomplete information. We give several examples of such nonlocal games where strategies that make use of entanglement…

Quantum Physics · Physics 2010-01-11 Richard Cleve , Peter Hoyer , Ben Toner , John Watrous

We investigate the expressive power of Higher-Order Datalog$^\neg$ under both the well-founded and the stable model semantics, establishing tight connections with complexity classes. We prove that under the well-founded semantics, for all…

Programming Languages · Computer Science 2026-01-14 Angelos Charalambidis , Babis Kostopoulos , Christos Nomikos , Panos Rondogiannis

Two essential ingredients of modern mixed-integer programming (MIP) solvers are diving heuristics that simulate a partial depth-first search in a branch-and-bound search tree and conflict analysis of infeasible subproblems to learn valid…

Optimization and Control · Mathematics 2019-02-08 Jakob Witzig , Ambros Gleixner

We give a new characterization of $\mathsf{NL}$ as the class of languages whose members have certificates that can be verified with small error in polynomial time by finite state machines that use a constant number of random bits, as…

Computational Complexity · Computer Science 2015-07-01 Cem Say , Abuzer Yakaryilmaz

State-of-the-art techniques for enhancing robustness of deep networks mostly rely on empirical risk minimization with suitable data augmentation. In this paper, we propose a complementary approach motivated by communication theory, aimed at…

Machine Learning · Computer Science 2024-03-05 Bhagyashree Puranik , Ahmad Beirami , Yao Qin , Upamanyu Madhow

Ensemble methods using multiple classifiers have proven to be the most successful approach for the task of Native Language Identification (NLI), achieving the current state of the art. However, a systematic examination of ensemble methods…

Computation and Language · Computer Science 2017-03-21 Shervin Malmasi , Mark Dras

Let A be an idempotent algebra on a finite domain. By mediating between results of Chen and Zhuk, we argue that if A satisfies the polynomially generated powers property (PGP) and B is a constraint language invariant under A (that is, in…

Computational Complexity · Computer Science 2021-06-25 Catarina Carvalho , Florent Madelaine , Barnaby Martin , Dmitriy Zhuk

We show that interactive protocols between a prover and a verifier, a well-known tool of complexity theory, can be used in practice to certify the correctness of automated reasoning tools. Theoretically, interactive protocols exist for all…

Logic in Computer Science · Computer Science 2023-09-07 Eszter Couillard , Philipp Czerner , Javier Esparza , Rupak Majumdar

Using an interactive theorem prover to reason about programs involves a sequence of interactions where the user challenges the theorem prover with conjectures. Invariably, many of the conjectures posed are in fact false, and users often…

Software Engineering · Computer Science 2011-10-24 Harsh Raju Chamarthi , Peter C. Dillinger , Matt Kaufmann , Panagiotis Manolios

Indexed loop scopes have been shown to be a helpful tool in creating sound loop invariant rules in dynamic logic for programming languages with abrupt completion, such as Java. These rules do not require program transformation of the loop…

Programming Languages · Computer Science 2020-02-10 Nathan Wasser , Dominic Steinhöfel

We propose an interactive multi-agent classifier that provides provable interpretability guarantees even for complex agents such as neural networks. These guarantees consist of lower bounds on the mutual information between selected…

Machine Learning · Computer Science 2024-03-25 Stephan Wäldchen , Kartikey Sharma , Berkant Turan , Max Zimmer , Sebastian Pokutta

We study the problem of finding Stackelberg equilibria in games with a massive number of players. So far, the only known game instances in which the problem is solved in polynomial time are some particular congestion games. However, a…

Computer Science and Game Theory · Computer Science 2019-05-31 Alberto Marchesi , Matteo Castiglioni , Nicola Gatti

This paper presents Diff-Explainer, the first hybrid framework for explainable multi-hop inference that integrates explicit constraints with neural architectures through differentiable convex optimization. Specifically, Diff-Explainer…

Computation and Language · Computer Science 2022-06-23 Mokanarangan Thayaparan , Marco Valentino , Deborah Ferreira , Julia Rozanova , André Freitas

As large language models become increasingly capable, it is critical that their outputs can be easily checked by less capable systems. Prover-verifier games can be used to improve checkability of model outputs, but display a degradation in…

Artificial Intelligence · Computer Science 2026-02-27 Yegon Kim , Juho Lee

We present an information theoretic proof of the nonsignalling multiprover parallel repetition theorem, a recent extension of its two-prover variant that underlies many hardness of approximation results. The original proofs used de Finetti…

Information Theory · Computer Science 2019-02-01 Himanshu Tyagi , Shun Watanabe

Neural networks are part of many contemporary NLP systems, yet their empirical successes come at the price of vulnerability to adversarial attacks. Previous work has used adversarial training and data augmentation to partially mitigate such…

Computation and Language · Computer Science 2019-12-23 Po-Sen Huang , Robert Stanforth , Johannes Welbl , Chris Dyer , Dani Yogatama , Sven Gowal , Krishnamurthy Dvijotham , Pushmeet Kohli

Majority voting over multiple LLM attempts improves mathematical reasoning, but correlated errors limit the effective sample size. A natural fix is to assign different reasoning strategies to different voters. The approach, Diverse Prompt…

Computation and Language · Computer Science 2026-04-17 Natapong Nitarach

We introduce a problem set-up we call the Iterated Matching Pennies (IMP) game and show that it is a powerful framework for the study of three problems: adversarial learnability, conventional (i.e., non-adversarial) learnability and…

Logic in Computer Science · Computer Science 2016-02-10 Michael Brand , David L. Dowe