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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 94019450 of 17610 papers

TitleStatusHype
Bring Your Own Data! Self-Supervised Evaluation for Large Language ModelsCode1
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language ModelsCode2
System-Level Natural Language FeedbackCode0
Retrieval-Pretrained Transformer: Long-range Language Modeling with Self-retrievalCode0
Knowledge-Infused Self Attention Transformers0
Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction0
Apolitical Intelligence? Auditing Delphi's responses on controversial political issues in the US0
Identifying and Extracting Rare Disease Phenotypes with Large Language ModelsCode0
Implicit spoken language diarization0
Generative Multimodal Entity LinkingCode1
AudioPaLM: A Large Language Model That Can Speak and Listen0
Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and OccupationsCode0
Mapping and Cleaning Open Commonsense Knowledge Bases with Generative TranslationCode0
Mass-Producing Failures of Multimodal Systems with Language ModelsCode1
FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair0
A Reference-less Quality Metric for Automatic Speech Recognition via Contrastive-Learning of a Multi-Language Model with Self-SupervisionCode1
NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive LearningCode1
OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and DialogueCode1
Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models for Non-language TasksCode0
Iterated Piecewise Affine (IPA) Approximation for Language Modeling0
Solving Dialogue Grounding Embodied Task in a Simulated Environment using Further Masked Language Modeling0
Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications0
A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysis0
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization PathsCode0
Lingua Manga: A Generic Large Language Model Centric System for Data Curation0
Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning0
Textbooks Are All You Need0
RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote SensingCode2
Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling0
Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion0
Sparse Modular Activation for Efficient Sequence ModelingCode1
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design0
Multilingual Few-Shot Learning via Language Model Retrieval0
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake NewsCode0
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving0
LM-VC: Zero-shot Voice Conversion via Speech Generation based on Language Models0
Evolutionary Verbalizer Search for Prompt-based Few Shot Text ClassificationCode0
Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge0
FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented DialogueCode0
Bloated Disclosures: Can ChatGPT Help Investors Process Information?0
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text GenerationCode0
LLMVA-GEBC: Large Language Model with Video Adapter for Generic Event Boundary CaptioningCode1
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation0
Scaling Open-Vocabulary Object DetectionCode0
Investigating Masking-based Data Generation in Language Models0
Clickbait Classification and Spoiling Using Natural Language Processing0
Data Selection for Fine-tuning Large Language Models Using Transferred Shapley ValuesCode0
Conformal Language ModelingCode1
ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation0
FALL-E: A Foley Sound Synthesis Model and StrategiesCode1
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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