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Kernelization is the standard framework to analyze preprocessing routines mathematically. Here, in terms of efficiency, we demand the preprocessing routine to run in time polynomial in the input size. However, today, various NP-complete…

Computational Complexity · Computer Science 2025-08-15 Hendrik Molter , Meirav Zehavi

This paper introduces a simple and scalable approach to improve the data efficiency of large language model (LLM) training by augmenting existing text data with thinking trajectories. The compute for pre-training LLMs has been growing at an…

Computation and Language · Computer Science 2025-10-20 Liang Wang , Nan Yang , Shaohan Huang , Li Dong , Furu Wei

Theorem provers are important tools for people working in formal verification. There are a myriad of interactive systems available today, with varying features and approaches motivating their development. These design choices impact their…

Logic in Computer Science · Computer Science 2025-09-19 Harrison Oates , Hyeonggeun Yun , Nikhila Gurusinghe

Parallel fixed-parameter tractability studies how parameterized problems can be solved in parallel. A surprisingly large number of parameterized problems admit a high level of parallelization, but this does not mean that we can also…

Computational Complexity · Computer Science 2018-07-11 Max Bannach , Till Tantau

What properties of a first-order search space support/hinder inference? What kinds of facts would be most effective to learn? Answering these questions is essential for understanding the dynamics of deductive reasoning and creating…

Artificial Intelligence · Computer Science 2025-02-04 Abhishek Sharma

The structure of transformation semigroups on a finite set is analyzed by introducing a hierarchy of functions mapping subsets to subsets. The resulting hierarchy of semigroups has a corresponding hierarchy of minimal ideals, or kernels.…

Probability · Mathematics 2016-12-02 G. Budzban , Ph. Feinsilver

The heat kernel expansion is a very convenient tool for studying one-loop divergences, anomalies and various asymptotics of the effective action. The aim of this report is to collect useful information on the heat kernel coefficients…

High Energy Physics - Theory · Physics 2008-11-26 D. V. Vassilevich

Agentic theorem provers combine a reasoning model, retrieval, search, and a proof assistant verifier, yet it remains unclear which components actually improve finite-budget proof success and why they help on real mathematical workloads. We…

Machine Learning · Statistics 2026-05-26 Sho Sonoda , Shunta Akiyama , Yuya Uezato

A query performance predictor estimates the retrieval effectiveness of an IR system for a given query. An important characteristic of QPP evaluation is that, since the ground truth retrieval effectiveness for QPP evaluation can be measured…

Information Retrieval · Computer Science 2022-02-15 Debasis Ganguly , Suchana Datta , Mandar Mitra , Derek Greene

A unique aspect of ColBERT is its use of [MASK] tokens in queries to score documents (query augmentation). Prior work shows [MASK] tokens weighting non-[MASK] query terms, emphasizing certain tokens over others , rather than introducing…

Information Retrieval · Computer Science 2024-08-27 Ben Giacalone , Richard Zanibbi

We present LISA, a proof system and proof assistant for constructing proofs in schematic first-order logic and axiomatic set theory. The logical kernel of the system is a proof checker for first-order logic with equality and schematic…

Logic in Computer Science · Computer Science 2025-07-16 Simon Guilloud , Sankalp Gambhir , Viktor Kunčak

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

Methodology · Statistics 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

Deep inference is a proof theoretic methodology that generalizes the standard notion of inference of the sequent calculus, whereby inference rules become applicable at any depth inside logical expressions. Deep inference provides more…

Logic in Computer Science · Computer Science 2015-07-01 Ozan Kahramanogullari

Prominently used in support vector machines and logistic regressions, kernel functions (kernels) can implicitly map data points into high dimensional spaces and make it easier to learn complex decision boundaries. In this work, by replacing…

Computation and Language · Computer Science 2019-10-29 Yingbo Gao , Christian Herold , Weiyue Wang , Hermann Ney

We present a general framework for hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of…

Methodology · Statistics 2021-02-03 Alexis Bellot , Mihaela van der Schaar

Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, yet existing evaluations focus almost exclusively on task accuracy and token savings.…

Computation and Language · Computer Science 2026-04-07 Lingjie Zeng , Xiaofan Chen , Yanbo Wang , Xiuying Chen

To adapt kernel two-sample and independence testing to complex structured data, aggregation of multiple kernels is frequently employed to boost testing power compared to single-kernel tests. However, we observe a phenomenon that directly…

Machine Learning · Computer Science 2025-10-14 Zhijian Zhou , Xunye Tian , Liuhua Peng , Chao Lei , Antonin Schrab , Danica J. Sutherland , Feng Liu

We use automated theorem provers to significantly shorten a formal development in higher order set theory. The development includes many standard theorems such as the fundamental theorem of arithmetic and irrationality of square root of…

Logic in Computer Science · Computer Science 2025-09-11 Chad E. Brown , Cezary Kaliszyk , Martin Suda , Josef Urban

Language models often generate long chain-of-thought traces, but it remains unclear how much of this reasoning is necessary for preserving the final prediction. We study this through the lens of overcomplete reasoning traces: generated…

Artificial Intelligence · Computer Science 2026-05-15 Sanjoy Chowdhury , Dinesh Manocha

Treebanks, such as the Penn Treebank (PTB), offer a simple approach to obtaining a broad coverage grammar: one can simply read the grammar off the parse trees in the treebank. While such a grammar is easy to obtain, a square-root rate of…

Computation and Language · Computer Science 2007-05-23 Alexander Krotov , Mark Hepple , Robert Gaizauskas , Yorick Wilks
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