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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 1185111900 of 17610 papers

TitleStatusHype
Explain and Conquer: Personalised Text-based Reviews to Achieve Transparency0
Embedding Hallucination for Few-Shot Language Fine-tuningCode0
Contrastive Learning for Prompt-Based Few-Shot Language LearnersCode1
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals0
OPT: Open Pre-trained Transformer Language ModelsCode5
Entity-aware Transformers for Entity SearchCode1
Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis0
Cue-bot: A Conversational Agent for Assistive Technology0
Fire Burns, Sword Cuts: Commonsense Inductive Bias for Exploration in Text-based GamesCode0
Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little CostCode1
-former: Infinite Memory TransformerCode1
Enhancing Chinese Pre-trained Language Model via Heterogeneous Linguistics GraphCode1
An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model TokenizersCode1
Exploiting Language Model Prompts Using Similarity Measures: A Case Study on the Word-in-Context Task0
Deep Neural Representations for Multiword Expressions DetectionCode0
Unsupervised Dependency Graph NetworkCode1
Phone-ing it in: Towards Flexible Multi-Modal Language Model Training by Phonetic Representations of DataCode0
Phrase-aware Unsupervised Constituency Parsing0
P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks0
KIQA: Knowledge-Infused Question Answering Model for Financial Table-Text Data0
Language Models as Context-sensitive Word Search EnginesCode0
The Best of both Worlds: Dual Channel Language modeling for Hope Speech Detection in low-resourced Kannada0
OPI@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text using RoBERTa Pre-trained Language ModelsCode1
SSN_ARMM@ LT-EDI -ACL2022: Hope Speech Detection for Equality, Diversity, and Inclusion Using ALBERT model0
Leveraging Similar Users for Personalized Language Modeling with Limited Data0
MR-P: A Parallel Decoding Algorithm for Iterative Refinement Non-Autoregressive Translation0
Tagging Without Rewriting: A Probabilistic Model for Unpaired Sentiment and Style Transfer0
Query Generation with External Knowledge for Dense Retrieval0
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction0
MTL-SLT: Multi-Task Learning for Spoken Language Tasks0
Thai Nested Named Entity Recognition CorpusCode1
The Xiaomi Text-to-Text Simultaneous Speech Translation System for IWSLT 20220
Joint Entity and Relation Extraction Based on Table Labeling Using Convolutional Neural NetworksCode1
Multi-Granularity Structural Knowledge Distillation for Language Model CompressionCode0
Stylistic Response Generation by Controlling Personality Traits and IntentCode0
Mix and Match: Learning-free Controllable Text Generationusing Energy Language ModelsCode1
Syntax-guided Contrastive Learning for Pre-trained Language Model0
ANNA”:" Enhanced Language Representation for Question Answering0
Improving Controllable Text Generation with Position-Aware Weighted Decoding0
DS-TOD: Efficient Domain Specialization for Task-Oriented DialogCode0
Challenges in including extra-linguistic context in pre-trained language models0
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification0
Cross-Modal Cloze Task: A New Task to Brain-to-Word DecodingCode0
Composing Structure-Aware Batches for Pairwise Sentence ClassificationCode0
Design principles of an open-source language modeling microservice package for AAC text-entry applications0
EICO: Improving Few-Shot Text Classification via Explicit and Implicit Consistency Regularization0
Cross-Lingual UMLS Named Entity Linking using UMLS Dictionary Fine-TuningCode0
Extracting Person Names from User Generated Text: Named-Entity Recognition for Combating Human Trafficking0
CueBot: Cue-Controlled Response Generation for Assistive Interaction Usages0
Improving Multiple Documents Grounded Goal-Oriented Dialog Systems via Diverse Knowledge Enhanced Pretrained Language Model0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified