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Related papers: Forbidden-Context & Ordered Grammar Systems

200 papers

In generative commonsense reasoning tasks such as CommonGen, generative large language models (LLMs) compose sentences that include all given concepts. However, when focusing on instruction-following capabilities, if a prompt specifies a…

Computation and Language · Computer Science 2025-06-19 Yusuke Sakai , Hidetaka Kamigaito , Taro Watanabe

Turkish has considerably freer word order than English. The interpretations of different word orders in Turkish rely on information that describes how a sentence relates to its discourse context. To capture the syntactic features of a free…

cmp-lg · Computer Science 2008-02-03 Beryl Hoffman

We consider a novel variant of the contextual bandit problem (i.e., the multi-armed bandit with side-information, or context, available to a decision-maker) where the context used at each decision may be corrupted ("useless context"). This…

Machine Learning · Computer Science 2020-06-30 Djallel Bouneffouf

Classic grammars and regular expressions can be used for a variety of purposes, including parsing, intent detection, and matching. However, the comparisons are performed at a structural level, with constituent elements (words or characters)…

Computation and Language · Computer Science 2018-08-16 David Wingate , William Myers , Nancy Fulda , Tyler Etchart

Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system which performs unrestricted word sense disambiguation (on all content words in free text) by combining…

cmp-lg · Computer Science 2007-05-23 Yorick Wilks , Mark Stevenson

Discrete diffusion models are a class of generative models that construct sequences by progressively denoising samples from a categorical noise distribution. Beyond their rapidly growing ability to generate coherent natural language, these…

Computation and Language · Computer Science 2025-12-11 Michael Cardei , Jacob K Christopher , Thomas Hartvigsen , Bhavya Kailkhura , Ferdinando Fioretto

Matrix grammars are one of the first approaches ever proposed in regulated rewriting, prescribing that rules have to be applied in a certain order. Originally, they have been introduced by \'Abrah\'am on linguistic grounds. In traditional…

Formal Languages and Automata Theory · Computer Science 2024-11-26 Henning Fernau , Lakshmanan Kuppusamy , Indhumathi Raman

Tree-controlled grammars are context-free grammars where the derivation process is controlled in such a way that every word on a level of the derivation tree must belong to a certain control language. We investigate the generative capacity…

Computational Complexity · Computer Science 2023-09-07 Bianca Truthe

Whether language models (LMs) have inductive biases that favor typologically frequent grammatical properties over rare, implausible ones has been investigated, typically using artificial languages (ALs) (White and Cotterell, 2021;…

Computation and Language · Computer Science 2025-10-15 Nadine El-Naggar , Tatsuki Kuribayashi , Ted Briscoe

The sequential structure of language, and the order of words in a sentence specifically, plays a central role in human language processing. Consequently, in designing computational models of language, the de facto approach is to present…

Computation and Language · Computer Science 2021-08-25 Rishi Bommasani

Existing works have studied the impacts of the order of words within natural text. They usually analyze it by destroying the original order of words to create a scrambled sequence, and then comparing the models' performance between the…

Computation and Language · Computer Science 2024-03-19 Qinghua Zhao , Jiaang Li , Lei Li , Zenghui Zhou , Junfeng Liu

Generating paragraphs of diverse contents is important in many applications. Existing generation models produce similar contents from homogenized contexts due to the fixed left-to-right sentence order. Our idea is permuting the sentence…

Computation and Language · Computer Science 2021-09-08 Wenhao Yu , Chenguang Zhu , Tong Zhao , Zhichun Guo , Meng Jiang

Majority of state-of-the-art deep learning methods are discriminative approaches, which model the conditional distribution of labels given inputs features. The success of such approaches heavily depends on high-quality labeled instances,…

Machine Learning · Computer Science 2019-09-13 Yanwu Xu , Mingming Gong , Junxiang Chen , Tongliang Liu , Kun Zhang , Kayhan Batmanghelich

Despite rapid advancement in the field of Constrained Natural Language Generation, little time has been spent on exploring the potential of language models which have had their vocabularies lexically, semantically, and/or phonetically…

Computation and Language · Computer Science 2023-06-29 Allen Roush , Sanjay Basu , Akshay Moorthy , Dmitry Dubovoy

Yes! In the present-day documenting and preserving endangered languages, the application of Large Language Models (LLMs) presents a promising approach. This paper explores how LLMs, particularly through in-context learning, can assist in…

Computation and Language · Computer Science 2024-12-17 Piyapath T Spencer , Nanthipat Kongborrirak

Graph data structures are fundamental for studying connected entities. With an increase in the number of applications where data is represented as graphs, the problem of graph generation has recently become a hot topic. However, despite its…

Probabilistic context-free grammars (PCFGs), which are commonly used to generate trees randomly, have been well analyzed theoretically, leading to applications in various domains. Despite their utility, the distributions that the grammar…

Disordered Systems and Neural Networks · Physics 2024-08-30 Kai Nakaishi , Koji Hukushima

We consider languages generated by weighted context-free grammars. It is shown that the behaviour of large texts is controlled by saddle-point equations for an appropriate generating function. We then consider ensembles of grammars, in…

Disordered Systems and Neural Networks · Physics 2022-10-03 Eric De Giuli

We continue our study of ordered context-free grammars, a grammar formalism that places an order on the parse trees produced by the corresponding context-free grammar. In particular, we simplify our previous definition of a derivation of a…

Formal Languages and Automata Theory · Computer Science 2023-09-19 Brink van der Merwe

This paper solves an open problem concerning the generative power of nonerasing context-free rewriting systems using a simple mechanism for checking for context dependencies, in the literature known as semi-conditional grammars of degree…

Formal Languages and Automata Theory · Computer Science 2010-04-22 Tomas Masopust