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Linear dependent types allow to precisely capture both the extensional behaviour and the time complexity of lambda terms, when the latter are evaluated by Krivine's abstract machine. In this work, we show that the same paradigm can be…

Logic in Computer Science · Computer Science 2012-07-25 Ugo Dal Lago , Barbara Petit

Strong call-by-need combines full normalization with the sharing discipline of lazy evaluation, yet no prior implementation achieved both simplicity and efficiency. We introduce RKNL, an abstract machine that realizes strong call-by-need…

Programming Languages · Computer Science 2026-03-24 Małgorzata Biernacka , Witold Charatonik , Tomasz Drab

Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become a powerful lever for improving large language model performance. Yet deploying these…

Machine Learning · Computer Science 2026-04-17 Zhiyuan Zhai , Bingcong Li , Bingnan Xiao , Ming Li , Xin Wang

Recently, Zaremba et al. demonstrated that increasing inference-time computation improves robustness in large proprietary reasoning LLMs. In this paper, we first show that smaller-scale, open-source models (e.g., DeepSeek R1, Qwen3,…

Artificial Intelligence · Computer Science 2025-07-23 Tong Wu , Chong Xiang , Jiachen T. Wang , Weichen Yu , Chawin Sitawarin , Vikash Sehwag , Prateek Mittal

We introduce a probabilistic extension of Levy's Call-By-Push-Value. This extension consists simply in adding a " flipping coin " boolean closed atomic expression. This language can be understood as a major generalization of Scott's PCF…

Logic in Computer Science · Computer Science 2023-06-22 Thomas Ehrhard , Christine Tasson

Otto's Theorem characterises the bisimulation-invariant PTIME queries over graphs as exactly those that can be formulated in the polyadic mu-calculus, hinging on the Immerman-Vardi Theorem which characterises PTIME (over ordered structures)…

Logic in Computer Science · Computer Science 2022-09-22 Florian Bruse , David Kronenberger , Martin Lange

Inference-time scaling has emerged as a powerful way to improve large language model (LLM) performance by generating multiple candidate responses and selecting among them. However, existing work on dynamic allocation for test-time compute…

Machine Learning · Computer Science 2025-09-15 Jenny Y. Huang , Mehul Damani , Yousef El-Kurdi , Ramon Astudillo , Wei Sun

The $\lambda$-calculus is a handy formalism to specify the evaluation of higher-order programs. It is not very handy, however, when one interprets the specification as an execution mechanism, because terms can grow exponentially with the…

Logic in Computer Science · Computer Science 2019-07-16 Andrea Condoluci , Beniamino Accattoli , Claudio Sacerdoti Coen

We propose the study of computing the Shapley value for a new class of cooperative games that we call budgeted games, and investigate in particular knapsack budgeted games, a version modeled after the classical knapsack problem. In these…

Computer Science and Game Theory · Computer Science 2014-09-19 Smriti Bhagat , Anthony Kim , S. Muthukrishnan , Udi Weinsberg

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

Control systems that satisfy temporal logic specifications have become increasingly popular due to their applicability to robotic systems. Existing control methods, however, are computationally demanding, especially when the problem size…

Systems and Control · Computer Science 2019-01-16 Lars Lindemann , Dimos V. Dimarogonas

We develop an efficient algorithm for weak recovery in a robust version of the stochastic block model. The algorithm matches the statistical guarantees of the best known algorithms for the vanilla version of the stochastic block model. In…

Machine Learning · Computer Science 2021-11-17 Jingqiu Ding , Tommaso d'Orsi , Rajai Nasser , David Steurer

Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoning: they apply fixed inference-time compute regardless of…

Skeletal call-by-need is an optimization of call-by-need evaluation also known as "fully lazy sharing": when the duplication of a value has to take place, it is first split into "skeleton", which is then duplicated, and "flesh" which is…

Logic in Computer Science · Computer Science 2025-09-24 Beniamino Accattoli , Francesco Magliocca , Loïc Peyrot , Claudio Sacerdoti Coen

This paper provides a call-by-name and a call-by-value term calculus, both of which have a Curry-Howard correspondence to the box fragment of the intuitionistic modal logic IK. The strong normalizability and the confluency of the calculi…

Logic in Computer Science · Computer Science 2016-06-17 Yoshihiko Kakutani

Robust estimation is much more challenging in high dimensions than it is in one dimension: Most techniques either lead to intractable optimization problems or estimators that can tolerate only a tiny fraction of errors. Recent work in…

Machine Learning · Computer Science 2018-03-14 Ilias Diakonikolas , Gautam Kamath , Daniel M. Kane , Jerry Li , Ankur Moitra , Alistair Stewart

A Variable Parameter (VP) analysis, that we introduce here, aims to give a precise algorithm time complexity expression in which an exponent appears solely in terms of a variable parameter. A variable parameter is the number of objects with…

Data Structures and Algorithms · Computer Science 2025-07-08 Nodari Vakhania

Substructural type systems, such as affine (and linear) type systems, are type systems which impose restrictions on copying (and discarding) of variables, and they have found many applications in computer science, including quantum…

Logic in Computer Science · Computer Science 2021-01-27 Vladimir Zamdzhiev

Test-time reasoning has raised benchmark performances and even shown promise in addressing the historically intractable problem of making models robust to adversarially out-of-distribution (OOD) data. Indeed, recent work used reasoning to…

Machine Learning · Computer Science 2026-03-27 Tavish McDonald , Bo Lei , Stanislav Fort , Bhavya Kailkhura , Brian Bartoldson

In the lambda calculus a term is solvable iff it is operationally relevant. Solvable terms are a superset of the terms that convert to a final result called normal form. Unsolvable terms are operationally irrelevant and can be equated…

Logic in Computer Science · Computer Science 2019-03-14 Á. García-Pérez , P. Nogueira
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