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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1150111550 of 17610 papers

TitleStatusHype
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge TransferCode1
Robustness Analysis of Video-Language Models Against Visual and Language PerturbationsCode0
ASR-Generated Text for Language Model Pre-training Applied to Speech Tasks0
Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic0
Egocentric Video-Language Pretraining @ Ego4D Challenge 2022Code2
BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language model0
Egocentric Video-Language Pretraining @ EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022Code2
Accurate RNA 3D structure prediction using a language model-based deep learning approachCode2
Revisiting Classifier: Transferring Vision-Language Models for Video RecognitionCode2
Probing via PromptingCode1
Generating Repetitions with Appropriate Repeated WordsCode0
UserLibri: A Dataset for ASR Personalization Using Only Text0
FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationales0
Intent Discovery for Enterprise Virtual Assistants: Applications of Utterance Embedding and Clustering to Intent Mining0
HATE-ITA: New Baselines for Hate Speech Detection in ItalianCode0
Exploring the Effect of Dialect Mismatched Language Models in Telugu Automatic Speech Recognition0
Self-supervised Product Title Rewrite for Product Listing Ads0
Minimally-Supervised Relation Induction from Pre-trained Language Model0
SwahBERT: Language Model of Swahili0
Mask and Regenerate: A Classifier-based Approach for Unpaired Sentiment Transformation of Reviews for Electronic Commerce Websites.0
Modal Dependency Parsing via Language Model PrimingCode0
MT-Speech at SemEval-2022 Task 10: Incorporating Data Augmentation and Auxiliary Task with Cross-Lingual Pretrained Language Model for Structured Sentiment Analysis0
L3i at SemEval-2022 Task 11: Straightforward Additional Context for Multilingual Named Entity Recognition0
SPDB Innovation Lab at SemEval-2022 Task 10: A Novel End-to-End Structured Sentiment Analysis Model based on the ERNIE-M0
niksss at SemEval-2022 Task 6: Are Traditionally Pre-Trained Contextual Embeddings Enough for Detecting Intended Sarcasm ?0
MarSan at SemEval-2022 Task 11: Multilingual complex named entity recognition using T5 and transformer encoderCode0
KroneckerBERT: Significant Compression of Pre-trained Language Models Through Kronecker Decomposition and Knowledge Distillation0
Learning Natural Language Generation with Truncated Reinforcement LearningCode0
JBNU-CCLab at SemEval-2022 Task 7: DeBERTa for Identifying Plausible Clarifications in Instructional Texts0
Language Model Augmented Monotonic Attention for Simultaneous Translation0
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Identifying Human Needs through Social Media: A study on Indian cities during COVID-19Code0
”Diversity and Uncertainty in Moderation” are the Key to Data Selection for Multilingual Few-shot Transfer0
CL-ReLKT: Cross-lingual Language Knowledge Transfer for Multilingual Retrieval Question AnsweringCode1
ConfliBERT: A Pre-trained Language Model for Political Conflict and ViolenceCode1
Clinical Flair: A Pre-Trained Language Model for Spanish Clinical Natural Language ProcessingCode0
HuaAMS at SemEval-2022 Task 8: Combining Translation and Domain Pre-training for Cross-lingual News Article Similarity0
Improving Classification of Infrequent Cognitive Distortions: Domain-Specific Model vs. Data Augmentation0
A Dog Is Passing Over The Jet? A Text-Generation Dataset for Korean Commonsense Reasoning and Evaluation0
Don’t Forget About Pronouns: Removing Gender Bias in Language Models Without Losing Factual Gender Information0
GPT-2-based Human-in-the-loop Theatre Play Script Generation0
Attention Fusion: a light yet efficient late fusion mechanism for task adaptation in NLU0
Exposing the Limits of Video-Text Models through Contrast SetsCode0
Empathetic Persuasion: Reinforcing Empathy and Persuasiveness in Dialogue Systems0
Infrrd.ai at SemEval-2022 Task 11: A system for named entity recognition using data augmentation, transformer-based sequence labeling model, and EnsembleCRF0
Beyond Characters: Subword-level Morpheme Segmentation0
Improving Conversational Recommendation Systems’ Quality with Context-Aware Item Meta-Information0
DANGNT-SGU at SemEval-2022 Task 11: Using Pre-trained Language Model for Complex Named Entity Recognition0
Data Augmentation with Dual Training for Offensive Span Detection0
A Self-supervised Joint Training Framework for Document Reranking0
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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