SOTAVerified

Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

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Showing 12901–12950 of 17610 papers

TitleStatusHype
PPL-MCTS: Constrained Textual Generation Through Discriminator-Guided MCTS DecodingCode1
Factorized Neural Transducer for Efficient Language Model AdaptationCode1
FQuAD2.0: French Question Answering and knowing that you know nothing—0
Fast-MD: Fast Multi-Decoder End-to-End Speech Translation with Non-Autoregressive Hidden IntermediatesCode3
Effective Use of Graph Convolution Network and Contextual Sub-Tree forCommodity News Event ExtractionCode1
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillationsCode1
XLM-K: Improving Cross-Lingual Language Model Pre-training with Multilingual KnowledgeCode1
Extracting and Inferring Personal Attributes from DialogueCode1
DziriBERT: a Pre-trained Language Model for the Algerian DialectCode1
Language Model Priming for Cross-Lingual Event Extraction—0
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation—0
A Proposal of Automatic Error Correction in Text—0
Identification of Enzymatic Active Sites with Unsupervised Language Modeling—0
MLIM: Vision-and-Language Model Pre-training with Masked Language and Image Modeling—0
Predicting Attention Sparsity in Transformers—0
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification—0
Cross-Lingual Language Model Meta-Pretraining—0
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach—0
Zero-Shot Information Extraction as a Unified Text-to-Triple TranslationCode1
BFClass: A Backdoor-free Text Classification Framework—0
Small-Bench NLP: Benchmark for small single GPU trained models in Natural Language ProcessingCode1
Low-Latency Incremental Text-to-Speech Synthesis with Distilled Context Prediction Network—0
Pix2seq: A Language Modeling Framework for Object DetectionCode1
DialogueBERT: A Self-Supervised Learning based Dialogue Pre-training Encoder—0
Distilling Relation Embeddings from Pre-trained Language Models—0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation—0
The Trade-offs of Domain Adaptation for Neural Language Models—0
TrOCR: Transformer-based Optical Character Recognition with Pre-trained ModelsCode1
BERTweetFR : Domain Adaptation of Pre-Trained Language Models for French Tweets—0
Influence of ASR and Language Model on Alzheimer's Disease Detection—0
JobBERT: Understanding Job Titles through SkillsCode1
Learning Natural Language Generation from Scratch—0
Adversarial Training with Contrastive Learning in NLP—0
Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition—0
Multilingual Molecular Representation Learning via Contrastive Pre-training—0
Commonsense Knowledge-Augmented Pretrained Language Models for Causal Reasoning Classification—0
BART-light: One Decoder Layer Is Enough—0
Machine Reading Comprehension: Generative or Extractive Reader?—0
Relating Neural Text Degeneration to Exposure Bias—0
Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy—0
SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis—0
Language Models as a Knowledge Source for Cognitive Agents—0
Primer: Searching for Efficient Transformers for Language ModelingCode0
Distilling Linguistic Context for Language Model CompressionCode1
Does Commonsense help in detecting Sarcasm?Code0
Exploring Multitask Learning for Low-Resource AbstractiveSummarization—0
Generative Pre-Training from MoleculesCode1
Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning—0
A Bag of Tricks for Dialogue Summarization—0
Regularized Training of Nearest Neighbor Language Models—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified