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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 92519300 of 17610 papers

TitleStatusHype
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning0
Using Term Position Similarity and Language Modeling for Bilingual Document Alignment0
Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens0
Using word embedding for bio-event extraction0
Using Word Embeddings for Automatic Query Expansion0
USTED: Improving ASR with a Unified Speech and Text Encoder-Decoder0
UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports0
UTA DLNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation0
UTFPR at WMT 2018: Minimalistic Supervised Corpora Filtering for Machine Translation0
Utilising a Large Language Model to Annotate Subject Metadata: A Case Study in an Australian National Research Data Catalogue0
Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation0
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications0
Utilizing ChatGPT to Enhance Clinical Trial Enrollment0
Utilizing Dependency Language Models for Graph-based Dependency Parsing Models0
UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation0
Utilizing Large Language Models for Information Extraction from Real Estate Transactions0
Utilizing Large Language Models for Natural Interface to Pharmacology Databases0
When Does Syntax Mediate Neural Language Model Performance? Evidence from Dropout Probes0
Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions0
Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance0
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes0
UVIS: Unsupervised Video Instance Segmentation0
UWAV at SemEval-2017 Task 7: Automated feature-based system for locating puns0
UW-BHI at MEDIQA 2019: An Analysis of Representation Methods for Medical Natural Language Inference0
Zero-shot Compound Expression Recognition with Visual Language Model at the 6th ABAW Challenge0
UXAgent: A System for Simulating Usability Testing of Web Design with LLM Agents0
UzbekTagger: The rule-based POS tagger for Uzbek language0
UzBERT: pretraining a BERT model for Uzbek0
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models0
V2X-REALM: Vision-Language Model-Based Robust End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling0
V3LMA: Visual 3D-enhanced Language Model for Autonomous Driving0
Unigram-Normalized Perplexity as a Language Model Performance Measure with Different Vocabulary Sizes0
Unfreeze with Care: Space-Efficient Fine-Tuning of Semantic Parsing Models0
VAIS ASR: Building a conversational speech recognition system using language model combination0
Zero-shot Composed Image Retrieval Considering Query-target Relationship Leveraging Masked Image-text Pairs0
WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain0
Unseen Attack Detection in Software-Defined Networking Using a BERT-Based Large Language Model0
Validating the Effectiveness of a Large Language Model-based Approach for Identifying Children's Development across Various Free Play Settings in Kindergarten0
X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects0
Unsupervised Dependency Graph Network0
Zero-shot Action Localization via the Confidence of Large Vision-Language Models0
Zero-resource Speech Translation and Recognition with LLMs0
VALLR: Visual ASR Language Model for Lip Reading0
When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment0
VALTEST: Automated Validation of Language Model Generated Test Cases0
When Large Language Model Meets Optimization0
UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human language0
UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion0
XDLM: Cross-lingual Diffusion Language Model for Machine Translation0
Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions0
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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