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We present Generative Logic (GL), a deterministic architecture that starts from user-supplied axiomatic definitions written in a minimalist Mathematical Programming Language (MPL) and systematically explores a configurable region of their…

Logic in Computer Science · Computer Science 2026-04-01 Nikolai Sergeev

Many language generation models are now available for a wide range of generation tasks, including machine translation and summarization. Combining such diverse models may lead to further progress, but ensembling generation models is…

Computation and Language · Computer Science 2022-10-31 Jungo Kasai , Keisuke Sakaguchi , Ronan Le Bras , Hao Peng , Ximing Lu , Dragomir Radev , Yejin Choi , Noah A. Smith

A finitary automaton group is a group generated by an invertible, deterministic finite-state letter-to-letter transducer whose only cycles are self-loops at an identity state. We show that, for this presentation of finite groups, the…

Formal Languages and Automata Theory · Computer Science 2024-03-13 Maximilian Kotowsky , Jan Philipp Wächter

Natural language understanding (NLU) and natural language generation (NLG) are two fundamental and related tasks in building task-oriented dialogue systems with opposite objectives: NLU tackles the transformation from natural language to…

Computation and Language · Computer Science 2020-06-16 Bo-Hsiang Tseng , Jianpeng Cheng , Yimai Fang , David Vandyke

The goal of generative phonology, as formulated by Chomsky and Halle (1968), is to specify a formal system that explains the set of attested phonological strings in a language. Traditionally, a collection of rules (or constraints, in the…

Computation and Language · Computer Science 2021-02-15 Shijie Wu , Edoardo Maria Ponti , Ryan Cotterell

Weighted automata are nondeterministic automata with numerical weights on transitions. They can define quantitative languages $L$ that assign to each word $w$ a real number $L(w)$. In the case of infinite words, the value of a run is…

Logic in Computer Science · Computer Science 2009-05-15 Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger

We investigate the number of sets of words that can be formed from a finite alphabet, counted by the total length of the words in the set. An explicit expression for the counting sequence is derived from the generating function, and…

Combinatorics · Mathematics 2010-01-26 Stefan Gerhold

In this paper we consider two classes of backward stochastic differential equations. Firstly, under a Lipschitz-type condition on the generator of the equation, which can also be unbounded, we give sufficient conditions for the existence of…

Probability · Mathematics 2018-03-08 Bujar Gashi , Jiajie Li

A subset S of a group G invariably generates G if G = <s^(g(s)) | s in S> for each choice of g(s) in G, s in S. In this paper we study invariable generation of infinite groups, with emphasis on linear groups. Our main result shows that a…

Group Theory · Mathematics 2014-07-18 William M. Kantor , Alexander Lubotzky , Aner Shalev

We study the problem of language identification in the limit, where given a sequence of examples from a target language, the goal of the learner is to output a sequence of guesses for the target language such that all the guesses beyond…

Computation and Language · Computer Science 2025-11-07 Moses Charikar , Chirag Pabbaraju , Ambuj Tewari

Natural language generation (NLG) spans a broad range of tasks, each of which serves for specific objectives and desires different properties of generated text. The complexity makes automatic evaluation of NLG particularly challenging.…

Computation and Language · Computer Science 2022-01-25 Mingkai Deng , Bowen Tan , Zhengzhong Liu , Eric P. Xing , Zhiting Hu

We prove that all finitely generated fully residually free groups (limit groups) have a sequence of finite dimensional unitary representations that `strongly converge' to the regular representation of the group. The corresponding statement…

Group Theory · Mathematics 2023-01-18 Larsen Louder , Michael Magee with Appendix by Will Hide , Michael Magee

Generic generation and manipulation of text is challenging and has limited success compared to recent deep generative modeling in visual domain. This paper aims at generating plausible natural language sentences, whose attributes are…

Machine Learning · Computer Science 2018-09-14 Zhiting Hu , Zichao Yang , Xiaodan Liang , Ruslan Salakhutdinov , Eric P. Xing

Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in…

Computation and Language · Computer Science 2026-05-12 R. Thomas McCoy

We explore from an algebraic viewpoint the properties of the tree languages definable with a first-order formula involving the ancestor predicate, using the description of these languages as those recognized by iterated block products of…

Formal Languages and Automata Theory · Computer Science 2018-12-06 Martin Beaudry

We address the non-redundant random generation of $k$ words of length $n$ in a context-free language. Additionally, we want to avoid a predefined set of words. We study a rejection-based approach, whose worst-case time complexity is shown…

Formal Languages and Automata Theory · Computer Science 2012-11-05 Andy Lorenz , Yann Ponty

This thesis presents a computational theory of unsupervised language acquisition, precisely defining procedures for learning language from ordinary spoken or written utterances, with no explicit help from a teacher. The theory is based…

cmp-lg · Computer Science 2008-02-03 Carl de Marcken

We study generic properties of topological groups in the sense of Baire category. First we investigate countably infinite (discrete) groups. We extend a classical result of B. H. Neumann, H. Simmons and A. Macintyre on algebraically closed…

Recently, there has been a surge in the use of generated data to enhance the performance of downstream models, largely due to the advancements in pre-trained language models. However, most prevailing methods trained generative and…

Computation and Language · Computer Science 2023-09-26 Tong Wu , Hao Wang , Zhongshen Zeng , Wei Wang , Hai-Tao Zheng , Jiaxing Zhang

Whether machines can originate novel content has been debated for nearly two centuries, from Lovelace's assertion that no engine can "originate anything" to Turing's question of whether a machine can amplify ideas brought in from outside.…

Multiagent Systems · Computer Science 2026-05-19 Weiyi Kong , Shiyang Lai , Jinghua Piao , James Evans