language models
A General Technique to Train Language Models on Language Models
... Language models often consist of a symbolic description of a language, such as a finite automaton (FA) or a context-free grammar (CFG), extended by a probability assignment to, for example, the ...
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Paraphrasing with Large Language Models
... One example of these large language models that has proven to be very good at text generation is GPT-2. It makes use of a transformer architec- ture and comes in various sizes up to 1.5 billion parameters. ...
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Efficient Subsampling for Training Complex Language Models
... entropy language models (MELM) and neural network language models ...multi-class language mod- eling problem is transformed into a set of bi- nary problems where each binary classifier ...
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A Posteriori Individual Word Language Models for Vietnamese Language
... statistical language models, one for each significant word of a language that contributes to the context of the ...word-domain language models is a precise domain model for the relevant ...
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Converting Continuous Space Language Models into N Gram Language Models for Statistical Machine Translation
... Language models are important in natural language processing tasks such as speech recognition and statistical machine ...n-gram language models (BNLMs) (Chen and Goodman, 1996; Chen and ...
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Temporal Analysis of Language through Neural Language Models
... traditional language models, NLMs in- volve predicting a set of future word given some history of previous ...guage models (wherein words are represented as indices in a vocabulary ...
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Half Context Language Models
... hierarchical language models (and a back-off variety [Zitouni 2007]) where each vocabulary item constitutes a leaf node in a word-tree, words are clustered into classes, and, in a recursive process, classes ...
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Language and Task Independent Text Categorization with Simple Language Models
... any language model can be used to perform text categorization based on ...n-gram models are extremely simple and have been found to be effective in many ...n-gram language models can be easily ...
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Language Models as Knowledge Bases?
... pretraining language mod- els on large textual corpora led to a surge of improvements for downstream NLP ...these models may also be storing relational knowl- edge present in the training data, and may be ...
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Stochastic Language Generation in Dialogue using Factored Language Models
... 7.1.1 Utterance Class LM Baseline. Oh and Rudnicky’s (O&R) approach trains a set of word-based n-gram language models (LMs) after replacing slot values by placeholder variables. In order to bias the LMs ...
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Towards Quantum Language Models
... Language models (LM) are basic tools in NLP used in various applications, such as Automatic Speech Recognition (ASR), machine translation, part-of-speech tagging, ...
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An Analysis of the Ability of Statistical Language Models to Capture the Structural Properties of Language
... neural language models in the frame- work of language ...neural models have been widely adopted, as they have empirically provided better ...the models and how they relate to real ...
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Shrinking Exponential Language Models
... exponential language models, ...tial language models by adding features (or a prior model) that shrink parameter values while maintain- ing training performance, and from this observa- tion we ...
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UNBNLP at SemEval 2019 Task 5 and 6: Using Language Models to Detect Hate Speech and Offensive Language
... employed language models to the problems of detecting hate speech and offen- sive language in social media ...to language model- ing including word-level n-gram and neural lan- guage ...
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Suffix Trees as Language Models
... SRI language model (SRILM) (Stolcke, 2002). Suffix array language models such as SALM (Zhang and Vogel, 2006) and (Stehouwer and Van Zaanen, 2010) were not compared due to time constraints, though a ...
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Exploiting Language Models for Visual Recognition
... different language models and build a general frame- work that is able to detect unseen actions through their components (verb - object - scene), hence our method does not limit the number of actions in im- ...
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Unsupervised morph segmentation and statistical language models for vocabulary expansion
... n-gram models (Trmal et al., 2014). Morph-based language models may be uti- lized using a constrained vocabulary as suggested in (Varjokallio and Kurimo, ...morph language mod- ...
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Dependency Language Models for Sentence Completion
... best-known language model based on depen- dency parsing is that of Chelba et ...The language mod- els we propose are far simpler to train and ...dency language model was proposed in Graham and van ...
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Convolutional Neural Network Language Models
... to language has received much less attention, and it has mainly focused on static classifica- tion tasks, such as sentence classification for Sentiment Analysis or relation ...to language modeling, a ...
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Language Models for Machine Translation: Original vs Translated Texts
... n-gram language models from various ...limit language models to a fixed vocabulary and map out-of-vocabulary (OOV) tokens to a unique symbol to better control the OOV rates amongvarious ...
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