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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1685116900 of 17610 papers

TitleStatusHype
Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability DetectionCode0
A Quick, trustworthy spectral knowledge Q&A system leveraging retrieval-augmented generation on LLMCode0
Can a large language model be a gaslighter?Code0
CR-UTP: Certified Robustness against Universal Text Perturbations on Large Language ModelsCode0
Enhancing Low-Resource NMT with a Multilingual Encoder and Knowledge Distillation: A Case StudyCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
Vocabulary-level Memory Efficiency for Language Model Fine-tuningCode0
Can AI Relate: Testing Large Language Model Response for Mental Health SupportCode0
Alleviating Sequence Information Loss with Data Overlapping and Prime Batch SizesCode0
Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LMCode0
Can (A)I Change Your Mind?Code0
Crowd Score: A Method for the Evaluation of Jokes using Large Language Model AI Voters as JudgesCode0
Cross-Refine: Improving Natural Language Explanation Generation by Learning in TandemCode0
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleCode0
Is It Navajo? Accurate Language Detection in Endangered Athabaskan LanguagesCode0
Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image GenerationCode0
AllenNLP Interpret: A Framework for Explaining Predictions of NLP ModelsCode0
A Quantum Many-body Wave Function Inspired Language Modeling ApproachCode0
Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted AttentionCode0
Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-ProfessionalsCode0
A Dutch Financial Large Language ModelCode0
Interpreting Biomedical VLMs on High-Imbalance Out-of-Distributions: An Insight into BiomedCLIP on RadiologyCode0
Cross-Modal Cloze Task: A New Task to Brain-to-Word DecodingCode0
Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure BuildingCode0
Improving Sequence Modeling Ability of Recurrent Neural Networks via SememesCode0
Abstractive Text Summarization based on Language Model Conditioning and Locality ModelingCode0
Cross-Lingual UMLS Named Entity Linking using UMLS Dictionary Fine-TuningCode0
FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the WildCode0
Enhancing RWKV-based Language Models for Long-Sequence Text GenerationCode0
A Linguistic Comparison between Human and ChatGPT-Generated ConversationsCode0
Alignment Analysis of Sequential Segmentation of Lexicons to Improve Automatic Cognate DetectionCode0
CamemBERT: a Tasty French Language ModelCode0
High-risk learning: acquiring new word vectors from tiny dataCode0
FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-gramsCode0
Calibrating LLM-Based EvaluatorCode0
CAiRE: An Empathetic Neural ChatbotCode0
Enhancing SPARQL Generation by Triplet-order-sensitive Pre-trainingCode0
Fusing Sentence Embeddings Into LSTM-based Autoregressive Language ModelsCode0
A Programmable Approach to Neural Network CompressionCode0
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic lossCode0
Interpreting Large Text-to-Image Diffusion Models with Dictionary LearningCode0
Future Language Modeling from Temporal Document HistoryCode0
FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented DialogueCode0
Highway NetworksCode0
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake NewsCode0
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model DecodingCode0
CABACE: Injecting Character Sequence Information and Domain Knowledge for Enhanced Acronym and Long-Form ExtractionCode0
Cross-Lingual Speaker Identification Using Distant SupervisionCode0
Coordinate-Aware Thermal Infrared Tracking Via Natural Language ModelingCode0
BvSP: Broad-view Soft Prompting for Few-Shot Aspect Sentiment Quad PredictionCode0
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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