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On bounded context-free languages
J. Inf. Process. Cybern., 1984Two new characterizations of bounded context-free languages are established and two known conjectures concerning context-free languages are shown to be true for the particular case of bounded context-free languages.
Michel Latteux, Gabriel Thierrin
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2007
In this paper, I present the class of linear context free languages (LCFLs) with a class of non-deterministic one-way two-head (read only) automata, called non-deterministic linear automata (NLA). At the begining of the work of an NLA, the reading heads are installed under the opposite ends of the given input string.
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In this paper, I present the class of linear context free languages (LCFLs) with a class of non-deterministic one-way two-head (read only) automata, called non-deterministic linear automata (NLA). At the begining of the work of an NLA, the reading heads are installed under the opposite ends of the given input string.
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In-Context Language Learning: Architectures and Algorithms
International Conference on Machine LearningLarge-scale neural language models exhibit a remarkable capacity for in-context learning (ICL): they can infer novel functions from datasets provided as input.
Ekin Akyürek +3 more
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Fundamenta Informaticae, 1986
We define a superclass of the class of context-free languages, denoted ACFL (almost context-free languages) and construct an infinite sequence of non-context-free languages of decreasing complexity, belonging to ACFL. The languages in ACFL share many important properties of context-free languages.
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We define a superclass of the class of context-free languages, denoted ACFL (almost context-free languages) and construct an infinite sequence of non-context-free languages of decreasing complexity, belonging to ACFL. The languages in ACFL share many important properties of context-free languages.
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SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
arXiv.orgWe propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal context without exceeding the token budget of commonly used LLMs.
Mingze Xu +7 more
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Neural Information Processing Systems
Instruction-based image editing enables precise modifications via natural language prompts, but existing methods face a precision-efficiency tradeoff: fine-tuning demands massive datasets (>10M) and computational resources, while training-free approaches
Zechuan Zhang +4 more
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Instruction-based image editing enables precise modifications via natural language prompts, but existing methods face a precision-efficiency tradeoff: fine-tuning demands massive datasets (>10M) and computational resources, while training-free approaches
Zechuan Zhang +4 more
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Kins of context-free languages
2005We study languages which can be described as limits of fast converging infinite sequences of context-free languages. Such a sequence \(L_0 \subseteq L_1 \subseteq L_2 \subseteq\) ... is fast converging if each string w of its limit language belongs to an Li which has a grammatical description very concise in comparison with the length of w .
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On the Density of Regular and Context-Free Languages
Discrete Mathematics, Algorithms and Applications, 2010The density of a language is defined as the function dL(n) = |L ∩ Σn| and counts the number of words of a certain length accepted by L. The study of the density of regular and context-free languages has attracted some attention culminating in the fact that such languages are either sparse, when the density can be bounded by a polynomial, or dense ...
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Noncounting Context-Free Languages
Journal of the ACM, 1978CRESPI REGHIZZI, STEFANO +2 more
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On Universally Polynomial Context-Free Languages
International Journal of Foundations of Computer Science, 2001A language is universally polynomial if its intersection with every NP-complete language is in P. Such a language would provide an automatic method for generating easy instances of intractable problems. In this note, we give a complete characterization of universally polynomial languages that are context-free, answering an open question in [4].
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