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- A Word Embedding Based Generalized Language Model for Information Retrieval
- Printed Text and Handwriting Recognition
- A Dynamic Language Model for Speech Recognition
- Korealbert: Pretraining a Lite BERT Model for Korean Language Understanding
- Natural Language Processing with Deep Learning Cs224n
- A Scalable Hierarchical Distributed Language Model
- A Generative Model of Words and Relationships from Multiple Sources
- Pre-Trained Word Embeddings for Indian Languages
- On Accelerating Training of Transformer-Based Language Models
- Using the Output Embedding to Improve Language Models
- Character-Level Language Modeling with Deeper Self-Attention
- GPT-3 Explainer: Putting GPT-3 Into Perspective
- Approaches for Neural-Network Language Model Adaptation
- Arxiv:2012.07805V2 [Cs.CR] 15 Jun 2021 Natural Language Processing Tasks
- Large-Scale N-Gram Language Models at Tencent
- Stanford's CS224D Notes
- Language Models (GPT, GPT-2 and GPT-3)
- Generating Text with Recurrent Neural Networks
- Improving Automatic Speech Recognition Output Via Noisy-Clean Phrase Context Modeling
- Recurrent Neural Network Language Model Adaptation for Conversational Speech Recognition
- Context Dependent Recurrent Neural Network Language Model
- A Structured Language Model
- Putting Words in Context: LSTM Language Models and Lexical Ambiguity
- BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding (Bidirectional Encoder Representations from Transformers)
- Language Models Are Unsupervised Multitask Learners
- Bertino: an Italian Distilbert Model
- The Postprocessing of Optical Character Recognition Based on Statistical Noisy Channel and Language Model
- Lecture 33: Smoothing N-Gram Language Models
- Extensions of Recurrent Neural Network Language Model
- Building Language Models with Fuzzy Weights
- Recurrent Neural Language Models
- A Neural Probabilistic Language Model
- Language Modeling
- Learning Transferable Visual Models from Natural Language Supervision
- Transformers for Large-Scale Language and Image Modeling
- Convolutional Neural Network Language Models
- New Module for Openai GPT-3 Creates Unique Images from Text 6 January 2021, by Bob Yirka
- A Simple Language Model for Task-Oriented Dialogue
- Pre-Training Language Representation (Elmo, BERT, Openai GPT)
- Language Models (GPT, GPT-2 and GPT-3) Advanced Techniques in Artificial Intelligence Jon Ander Almandoz, Julen Etxaniz and Jokin Rodriguez 2020-09-28
- N-Gram Language Models
- Probabilistic Language Models 1.0
- A Review of Arabic Optical Character Recognition Techniques & Performance
- Topic Compositional Neural Language Model
- The Evolution of Language Models Applied to Emotion Analysis of Arabic Tweets
- Recurrent NN 1
- Approach for Machine-Printed Arabic Character Recognition: The-State-Of-The-Art Deep-Learning Method
- N-Gram Language Models
- With Deep Learning CS224N/ Ling284
- Arxiv:2103.06561V6 [Cs.CV] 8 Jul 2021
- Machine Learning for Language Modelling Part 4: Neural Network LM Optimisation
- Gated Word-Character Recurrent Language Model
- Evaluating Word Embedding Models: Methods and Experimental Results
- Release Strategies and the Social Impacts of Language Models
- Deep Learning in Natural Language Processing
- Natural Language Processing with Deep Learning CS224N/Ling284
- Understanding the Capabilities, Limitations, and Societal Impact Of
- Arxiv:1906.03591V2 [Cs.CL] 13 Jun 2019 Where Wi Denotes I-Th Word in the Sequence S
- Using Language Modelling to Integrate Speech Recognition with a Flat Semantic Analysis
- Distributed Representations of Words and Phrases and Their Compositionality
- GPT-Too: a Language-Model-First Approach for AMR-To-Text Generation
- Joint Language and Translation Modeling with Recurrent Neural Networks
- Large Scale Language Modeling in Automatic Speech Recognition Ciprian Chelba, Dan Bikel, Maria Shugrina, Patrick Nguyen, Shankar Kumar
- N-Gram Language Models
- Neural Networks Language Models
- Recurrent Neural Networks for Language Understanding
- Improving Language Generation with Sentence Coherence Objective
- Definition Modeling: Learning to Define Word Embeddings In
- A Comparison of Word-Based and Context-Based Representations for Classification Problems in Health Informatics
- Effective Sentence Scoring Method Using BERT for Speech Recognition
- Cross-Lingual Language Model Pretraining
- Language Models Are Few-Shot Learners
- Introduction to N-‐Grams
- 3 Language Models 1: N-Gram Language Models
- A Neural Probabilistic Language Model
- Contextual BERT: Conditioning the Language Model Using a Global State
- Language Modelling for Handwriting Recognition Wassim Swaileh
- MLM) - Select 15% Random Words in the Input
- Pre-Trained Models for Natural Language Processing: a Survey