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Theory revision integrates inductive learning and background knowledge by combining training examples with a coarse domain theory to produce a more accurate theory. There are two challenges that theory revision and other theory-guided…

Artificial Intelligence · Computer Science 2008-02-03 S. K. Donoho , L. A. Rendell

RP-Rewriter (Retain-Property) is a verified clause processor that can use some of the existing ACL2 rewrite rules to prove conjectures through term rewriting. Optimized for conjectures that can expand into large terms, the rewriter tries to…

Logic in Computer Science · Computer Science 2020-09-30 Mertcan Temel

Logically constrained term rewriting is a rewriting framework that supports built-in data structures such as integers and bit vectors. Recently, constrained terms play a key role in various analyses and applications of logically constrained…

Logic in Computer Science · Computer Science 2025-12-16 Kanta Takahata , Jonas Schöpf , Naoki Nishida , Takahito Aoto

Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation. However, as LLMs are primarily trained on final text results rather than intermediate revisions, it might…

Computation and Language · Computer Science 2023-12-21 Lei Shu , Liangchen Luo , Jayakumar Hoskere , Yun Zhu , Yinxiao Liu , Simon Tong , Jindong Chen , Lei Meng

Non-autoregressive models greatly improve decoding speed over typical sequence-to-sequence models, but suffer from degraded performance. Infilling and iterative refinement models make up some of this gap by editing the outputs of a…

Audio and Speech Processing · Electrical Eng. & Systems 2020-10-28 Ethan A. Chi , Julian Salazar , Katrin Kirchhoff

Evaluating natural language generation systems is challenging due to the diversity of valid outputs. While human evaluation is the gold standard, it suffers from inconsistencies, lack of standardisation, and demographic biases, limiting…

Computation and Language · Computer Science 2025-09-11 Hanhua Hong , Chenghao Xiao , Yang Wang , Yiqi Liu , Wenge Rong , Chenghua Lin

Prompting methods recently achieve impressive success in few-shot learning. These methods modify input samples with prompt sentence pieces, and decode label tokens to map samples to corresponding labels. However, such a paradigm is very…

Computation and Language · Computer Science 2022-04-05 Yutai Hou , Cheng Chen , Xianzhen Luo , Bohan Li , Wanxiang Che

New approach to systems of polynomial recursions is developed based on the Carleman linearization procedure. The article is divided into two main sections: firstly, we focus on the case of uni-variable depth-one polynomial recurrences.…

Dynamical Systems · Mathematics 2021-12-16 Mikołaj Myszkowski

This paper introduces a new term rewriting system that is similar to the embedded read-back mechanism for interaction nets presented in our previous work, but is easier to follow than in the original setting and thus to analyze its…

Logic in Computer Science · Computer Science 2018-08-21 Anton Salikhmetov

The goal of this work is to recover articulatory information from the speech signal by acoustic-to-articulatory inversion. One of the main difficulties with inversion is that the problem is underdetermined and inversion methods generally…

Computation and Language · Computer Science 2007-05-23 Blaise Potard , Yves Laprie

A series of works has established rewriting as an essential tool in order to prove coherence properties of algebraic structures, such as MacLane's coherence theorem for monoidal categories, based on the observation that, under reasonable…

Category Theory · Mathematics 2025-07-30 Samuel Mimram

Circuit representations are becoming the lingua franca to express and reason about tractable generative and discriminative models. In this paper, we show how complex inference scenarios for these models that commonly arise in machine…

Machine Learning · Statistics 2021-02-12 Antonio Vergari , YooJung Choi , Anji Liu , Stefano Teso , Guy Van den Broeck

Counterfactual instances are a powerful tool to obtain valuable insights into automated decision processes, describing the necessary minimal changes in the input space to alter the prediction towards a desired target. Most previous…

Machine Learning · Computer Science 2021-06-07 Robert-Florian Samoilescu , Arnaud Van Looveren , Janis Klaise

Language tasks involving character-level manipulations (e.g., spelling corrections, arithmetic operations, word games) are challenging for models operating on subword units. To address this, we develop a causal intervention framework to…

Computation and Language · Computer Science 2023-12-20 Jing Huang , Zhengxuan Wu , Kyle Mahowald , Christopher Potts

Large transformer-based language models have been shown to be very effective in many classification tasks. However, their computational complexity prevents their use in applications requiring the classification of a large set of candidates.…

Computation and Language · Computer Science 2020-05-08 Luca Soldaini , Alessandro Moschitti

Just because some purely recurrent models suffer from being hard to optimize and inefficient on today's hardware, they are not necessarily bad models of language. We demonstrate this by the extent to which these models can still be improved…

Computation and Language · Computer Science 2023-04-19 Gábor Melis

Motivated by questions from program transformations, eight notions of isomorphisms between term rewriting systems are defined, analysed, and classified. The notions include global isomorphisms, where the renaming of variables and function…

Logic in Computer Science · Computer Science 2022-12-01 Michael Christian Fink Amores , David Sabel

Most expressivity results for transformers treat them as language recognizers -- devices that accept or reject strings -- rather than as they are used in practice: as language models that generate strings autoregressively and…

Computation and Language · Computer Science 2026-05-26 Andy Yang , Anej Svete , Jiaoda Li , Anthony Widjaja Lin , Jonathan Rawski , Ryan Cotterell , David Chiang

In this article we investigate how a subterm pattern matching algorithm can be exploited to implement efficient term rewriting procedures. From the left-hand sides of the rewrite system we construct a set automaton, which can be used to…

Computation and Language · Computer Science 2023-04-07 Mark Bouwman , Rick Erkens

Process calculi and graph transformation systems provide models of reactive systems with labelled transition semantics. While the semantics for process calculi is compositional, this is not the case for graph transformation systems, in…

Logic in Computer Science · Computer Science 2011-08-03 Andrei Dorman , Tobias Heindel