Results 51 to 60 of about 1,205,220 (192)

Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones [PDF]

open access: yes, 2017
Syllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware model ...
Assylbekov, Zhenisbek   +3 more
core   +4 more sources

Language modeling using X-grams [PDF]

open access: yes, 1996
In this paper, an extension of n-grams, called x-grams, is proposed. In this extension, the memory of the model (n) is not fixed a priori. Instead, large memories are accepted first, and merging criteria are then applied to reduce the complexity and to ...
Bonafonte Cávez, Antonio   +1 more
core   +1 more source

Watermarking Language Models through Language Models

open access: yesIEEE Transactions on Artificial Intelligence
Watermarking the outputs of large language models (LLMs) is critical for provenance tracing, content regulation, and model accountability. Existing approaches often rely on access to model internals or are constrained by static rules and token-level perturbations.
Dasgupta, Agnibh   +2 more
openaire   +2 more sources

X-RMTV: An Integrated Approach for Requirement Modeling, Traceability Management, and Verification in MBSE

open access: yesSystems
Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and ...
Pengfei Gu   +6 more
doaj   +1 more source

A model transformation framework to increase OCL usability

open access: yesJournal of King Saud University: Computer and Information Sciences, 2016
The usability of a modeling language has a direct relationship with several factors of models constructed with the modeling language, such as time required and accuracy.
Samin Salemi   +2 more
doaj   +1 more source

Language Modeling by Language Models

open access: yes
Can we leverage LLMs to model the process of discovering novel language model (LM) architectures? Inspired by real research, we propose a multi-agent LLM approach that simulates the conventional stages of research, from ideation and literature search (proposal stage) to design implementation (code generation), generative pre-training, and downstream ...
Cheng, Junyan   +2 more
openaire   +2 more sources

Towards a continuous modeling of natural language domains

open access: yes, 2016
Humans continuously adapt their style and language to a variety of domains. However, a reliable definition of `domain' has eluded researchers thus far. Additionally, the notion of discrete domains stands in contrast to the multiplicity of heterogeneous ...
Breslin, John G.   +2 more
core   +1 more source

Synchronous models of language [PDF]

open access: yesProceedings of the 34th annual meeting on Association for Computational Linguistics -, 1996
In synchronous rewriting, the productions of two rewriting systems are paired and applied synchronously in the derivation of a pair of strings. We present a new synchronous rewriting system and argue that it can handle certain phenomena that are not covered by existing synchronous systems.
RAMBOW O., SATTA, GIORGIO
openaire   +3 more sources

Semantic Modeling Approach Supporting Process Modeling and Analysis in Aircraft Development

open access: yesApplied Sciences, 2022
With the increasing complexity of aircraft development programs, the development processes of aircraft and their subsystems are continuously becoming complicated, leading to the growing risks of development cost across the entire life cycle.
Junda Ma   +5 more
doaj   +1 more source

Language modeling and transcription of the TED corpus lectures [PDF]

open access: yes, 2003
Transcribing lectures is a challenging task, both in acoustic and in language modeling. In this work, we present our first results on the automatic transcription of lectures from the TED corpus, recently released by ELRA and LDC.
Cettolo, M., Federico, M., Leeuwis, E.
core   +1 more source

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