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Reading a document and extracting an answer to a question about its content has attracted substantial attention recently. While most work has focused on the interaction between the question and the document, in this work we evaluate the…

Computation and Language · Computer Science 2018-09-05 Shimi Salant , Jonathan Berant

Reconfigurable interaction induces another dimension of nondeterminism in concurrent systems which makes it hard to reason about the different choices of the system from a global perspective. Namely, (1) choices that correspond to…

Logic in Computer Science · Computer Science 2021-08-02 Yehia Abd Alrahman , Mauricio Martel , Nir Piterman

Linear logic Concurrent Constraint programming (LCC) is an extension of concurrent constraint programming (CC) where the constraint system is based on Girard's linear logic instead of the classical logic. In this paper we address the…

Programming Languages · Computer Science 2011-08-02 Rémy Haemmerlé

We phrase parsing with context-free expressions as a type inhabitation problem where values are parse trees and types are context-free expressions. We first show how containment among context-free and regular expressions can be reduced to a…

Formal Languages and Automata Theory · Computer Science 2017-08-25 Martin Sulzmann , Peter Thiemann

Designers of autonomous agents, whether in physical or virtual environments, need to express nondeterminisim, failure, and parallelism in behaviors, as well as accounting for synchronous coordination between agents. Behavior Trees are a…

Programming Languages · Computer Science 2018-03-28 Chris Martens , Eric Butler , Joseph C. Osborn

Types-and-effects are type systems, which allow one to express general semantic properties and to statically reason about program's execution. They have been widely exploited to specify static analyses, for example to track computational…

Logic in Computer Science · Computer Science 2011-08-12 Letterio Galletta , Giorgio Levi

Scaling large language models (LLMs) leads to an emergent capacity to learn in-context from example demonstrations. Despite progress, theoretical understanding of this phenomenon remains limited. We argue that in-context learning relies on…

Computation and Language · Computer Science 2023-03-15 Michael Hahn , Navin Goyal

Contextual memory integration remains a high challenge in the development of language models, particularly in tasks that require maintaining coherence over extended sequences. Traditional approaches, such as self-attention mechanisms and…

Computation and Language · Computer Science 2025-08-11 George Applegarth , Christian Weatherstone , Maximilian Hollingsworth , Henry Middlebrook , Marcus Irvin

This paper presents a theory for the refinement of shared-memory concurrent algorithms from specifications. We augment pre and post condition specifications with Jones' rely and guarantee conditions, all of which are encoded as commands…

Logic in Computer Science · Computer Science 2023-09-12 Ian J. Hayes , Larissa A. Meinicke , Patrick A. Meiring

We propose a novel dependency-based hybrid tree model for semantic parsing, which converts natural language utterance into machine interpretable meaning representations. Unlike previous state-of-the-art models, the semantic information is…

Computation and Language · Computer Science 2018-09-05 Zhanming Jie , Wei Lu

Logical relations constitute a key method for reasoning about contextual equivalence of programs in higher-order languages. They are usually developed on a per-case basis, with a new theory required for each variation of the language or of…

Logic in Computer Science · Computer Science 2024-05-17 Sergey Goncharov , Stefan Milius , Stelios Tsampas , Henning Urbat

Strategic coopetition in multi-stakeholder systems requires understanding how cooperation persists through time without binding contracts. This technical report extends computational foundations for strategic coopetition to sequential…

Multiagent Systems · Computer Science 2026-04-03 Vik Pant , Eric Yu

In-context reinforcement learning (ICRL) refers to the ability of RL agents to adapt to new tasks at inference time without parameter updates by conditioning on additional context. Recent empirical studies further demonstrate that…

Machine Learning · Computer Science 2026-05-11 Zixuan Xie , Xinyu Liu , Rohan Chandra , Shangtong Zhang

Human conversation relies heavily on conversational implicature, in which speakers convey meanings that are suggested rather than explicitly stated. Although recent large language models exhibit strong conversational fluency, they remain…

Computation and Language · Computer Science 2026-05-26 Hirona Jacqueline Arai , Xiang Ren

The article bridges between two major paradigms in computation, the functional, at basis computation from input to output, and the interactive, where computation reacts to its environment while underway. Central to any compositional theory…

Programming Languages · Computer Science 2023-04-11 Glynn Winskel

In this paper, we study the complexity of execution in higher-order programming languages. Our study has two facets: on the one hand we give an upper bound to the length of interactions between bounded P-visible strategies in Hyland-Ong…

Logic in Computer Science · Computer Science 2017-01-11 Pierre Clairambault

Recent work has demonstrated the effectiveness of formulating decision making as supervised learning on offline-collected trajectories. Powerful sequence models, such as GPT or BERT, are often employed to encode the trajectories. However,…

Machine Learning · Computer Science 2023-10-31 Zilai Zeng , Ce Zhang , Shijie Wang , Chen Sun

The mathematical formalism of quantum theory exhibits significant effectiveness when applied to cognitive phenomena that have resisted traditional (set theoretical) modeling. Relying on a decade of research on the operational foundations of…

We investigate program equivalence for linear higher-order(sequential) languages endowed with primitives for computational effects. More specifically, we study operationally-based notions of program equivalence for a linear…

Programming Languages · Computer Science 2021-06-25 Ugo Dal Lago , Francesco Gavazzo

Word representations induced from models with discrete latent variables (e.g.\ HMMs) have been shown to be beneficial in many NLP applications. In this work, we exploit labeled syntactic dependency trees and formalize the induction problem…

Computation and Language · Computer Science 2016-02-08 Simon Šuster , Gertjan van Noord , Ivan Titov