Context-free grammar ≈ Context-free grammar
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Head-Driven Phrase Structure Grammar Parsing on Penn Treebank Open
Head-driven phrase structure grammar (HPSG) enjoys a uniform formalism representing rich contextual syntactic and even semantic meanings. This paper makes the first attempt to formulate a simplified HPSG by integrating constituent and depe…
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Compound Probabilistic Context-Free Grammars for Grammar Induction Open
We study a formalization of the grammar induction problem that models sentences as being generated by a compound probabilistic context free grammar. In contrast to traditional formulations which learn a single stochastic grammar, our conte…
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Recurrent Neural Network Grammars Open
We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experiments show that…
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Synthesizing program input grammars Open
We present an algorithm for synthesizing a context-free grammar encoding the language of valid program inputs from a set of input examples and blackbox access to the program. Our algorithm addresses shortcomings of existing grammar inferen…
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Practical Dynamic Grammars for Dynamic Languages Open
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How Grammars Grow: Argument Structure and the Acquisition of Non-Basic Syntax Open
This dissertation examines the acquisition of argument structure as a window into the role of development in grammar learning. The way that children represent the data for language acquisition depends on the grammatical knowledge they have…
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Large Language Models as General Pattern Machines Open
We observe that pre-trained large language models (LLMs) are capable of autoregressively completing complex token sequences -- from arbitrary ones procedurally generated by probabilistic context-free grammars (PCFG), to more rich spatial p…
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Do collocational frameworks have local grammars? Open
This study extends the theory of local grammars by making the case that local grammars can also be employed to better and more fully describe the patterns of co-selection found in collocational frameworks (Renouf & Sinclair 1991). The term…
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Probabilistic grammars for equation discovery Open
Equation discovery, also known as symbolic regression, is a type of automated\nmodeling that discovers scientific laws, expressed in the form of equations,\nfrom observed data and expert knowledge. Deterministic grammars, such as\ncontext-…
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REINAM: reinforcement learning for input-grammar inference Open
Program input grammars (i.e., grammars encoding the language of valid program inputs) facilitate a wide range of applications in software engineering such as symbolic execution and delta debugging. Grammars synthesized by existing approach…
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An introduction to tag sequence grammars and the RASP system parser Open
This report describes the tag sequence grammars released as part of the Robust Accurate Statistical Parsing (RASP) system. It is intended to help users of RASP understand the linguistic and engineering rationale behind the grammars and pre…
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Representing and Learning Grammars in Answer Set Programming Open
In this paper we introduce an extension of context-free grammars called answer set grammars (ASGs). These grammars allow annotations on production rules, written in the language of Answer Set Programming (ASP), which can express context-se…
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Weighted Hierarchical Grammatical Evolution Open
Grammatical evolution (GE) is one of the most widespread techniques in evolutionary computation. Genotypes in GE are bit strings while phenotypes are strings, of a language defined by a user-provided context-free grammar. In this paper, we…
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Simplicity and the form of grammars Open
The goal of theory construction is explanation: for language, theory for particular languages (grammar) and for the faculty of language FoL (the innate endowment for language acquisition). A primitive notion of simplicity of grammars is nu…
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Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing Open
One of the limitations of semantic parsing approaches to open-domain question\nanswering is the lexicosyntactic gap between natural language questions and\nknowledge base entries -- there are many ways to ask a question, all with the\nsame…
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Efficient Guided Generation for Large Language Models Open
In this article we show how the problem of neural text generation can be constructively reformulated in terms of transitions between the states of a finite-state machine. This framework leads to an efficient approach to guiding text genera…
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A Uniform Framework for Problems on Context-Free Grammars Open
In a paper published in Information Processing Letters in 2000, Bouajjani et al. presented an automata-based approach to a number of elementary problems on context-free grammars. This approach is of pedagogical interest since it provides a…
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A CCG-Based Version of the DisCoCat Framework Open
While the DisCoCat model (Coecke et al., 2010) has been proved a valuable tool for studying compositional aspects of language at the level of semantics, its strong dependency on pregroup grammars poses important restrictions: first, it pre…
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Defining Models - Meta Models versus Graph Grammars Open
The precise specification of software models is a major concern in model-driven design of object-oriented software. Metamodelling and graph grammars are apparent choices for such specifications. Metamodelling has several advantages: it is …
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PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols Open
Probabilistic context-free grammars (PCFGs) with neural parameterization have been shown to be effective in unsupervised phrase-structure grammar induction. However, due to the cubic computational complexity of PCFG representation and pars…
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Syntax error recovery in parsing expression grammars Open
Parsing Expression Grammars (PEGs) are a formalism used to describe top-down\nparsers with backtracking. As PEGs do not provide a good error recovery\nmechanism, PEG-based parsers usually do not recover from syntax errors in the\ninput, or…
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A typed, algebraic approach to parsing Open
In this paper, we recall the definition of the context-free expressions (or µ-regular expressions), an algebraic presentation of the context-free languages. Then, we define a core type system for the context-free expressions which gives a …
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Practical, general parser combinators Open
Parser combinators are a popular approach to parsing where contextfree grammars are represented as executable code. However, conventional parser combinators do not support left recursion, and can have worst-case exponential runtime. These …
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A Sound and Complete Left-Corner Parsing for Minimalist Grammars Open
This paper presents a left-corner parser for minimalist grammars. The relation between the parser and the grammar is transparent in the sense that there is a very simple 1-1 correspondence between derivations and parses. Like left-corner c…
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The Neural Network Pushdown Automaton: Model, Stack and Learning Simulations Open
In order for neural networks to learn complex languages or grammars, they must have sufficient computational power or resources to recognize or generate such languages. Though many approaches have been discussed, one ob- vious approach to …
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Learning attribute grammars for movement primitive sequencing Open
Movement primitives are a well studied and widely applied concept in modern robotics. However, composing primitives out of an existing library has shown to be a challenging problem. We propose the use of probabilistic context-free grammars…
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Generating Context-Free Grammars using Classical Planning Open
This paper presents a novel approach for generating Context-Free Grammars (CFGs) from small sets of input strings (a single input string in some cases). Our approach is to compile this task into a classical planning problem whose solutions…
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Towards Theorem Proving Graph Grammars using Event-B Open
Graph grammars may be used as specification technique for different kinds of systems, specially in situations in which states are complex structures that can be adequately modeled as graphs (possibly with an attribute data part) and in whi…
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$$\sigma $$GTTM III: Learning-Based Time-Span Tree Generator Based on PCFG Open
An automatic analyzer based on the generative theory of tonal music (GTTM) for acquiring a time-span tree is described. Although an analyzer based on GTTM was previously reported, it requires manually manipulating 46 adjustable parameters …
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Petri Net Controlled Grammars: the Case of Special Petri Nets Open
A Petri net controlled grammar is a context-free grammar equipped with a Petri net, whose transitions are labeled with rules of the grammar or the empty string, and the associated language consists of all terminal strings which can be deri…