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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 65016550 of 17610 papers

TitleStatusHype
Automatic Post-Editing for the DiscoMT Pronoun Translation Task0
Automatic Proficiency Assessment in L2 English Learners0
Automatic Prompt Generation and Grounding Object Detection for Zero-Shot Image Anomaly Detection0
Learning to Rewrite Prompts for Personalized Text Generation0
Automatic Speech Recognition for Humanitarian Applications in Somali0
Automatic Speech Recognition for Irish: the ABAIR-ÉIST System0
Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model0
Automatic Speech Recognition of African American English: Lexical and Contextual Effects0
Automatic Speech Recognition on a Firefighter TETRA Broadcast Channel0
Automatic Speech Summarisation: A Scoping Review0
Automatic Spoken Language Identification using a Time-Delay Neural Network0
Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning0
Automatic Text Summarization (ATS) for Research Documents in Sorani Kurdish0
Automatic Transliteration of Romanized Dialectal Arabic0
Towards Automatic Construction of Filipino WordNet: Word Sense Induction and Synset Induction Using Sentence Embeddings0
Automatic Word Segmentation and Part-of-Speech Tagging of Ancient Chinese Based on BERT Model0
Automating Date Format Detection for Data Visualization0
Automating Knowledge Acquisition for Content-Centric Cognitive Agents Using LLMs0
Automating Mathematical Proof Generation Using Large Language Model Agents and Knowledge Graphs0
Automating psychological hypothesis generation with AI: when large language models meet causal graph0
Automating PTSD Diagnostics in Clinical Interviews: Leveraging Large Language Models for Trauma Assessments0
Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning0
Automating Security Audit Using Large Language Model based Agent: An Exploration Experiment0
Automating speech reception threshold measurements using automatic speech recognition0
Automating the Analysis of Public Saliency and Attitudes towards Biodiversity from Digital Media0
Automating Thought of Search: A Journey Towards Soundness and Completeness0
AutoML-GPT: Large Language Model for AutoML0
Auto-MLM: Improved Contrastive Learning for Self-supervised Multi-lingual Knowledge Retrieval0
Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology0
Autonomous Behavior Planning For Humanoid Loco-manipulation Through Grounded Language Model0
Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model0
Autonomous Large Language Model Agents Enabling Intent-Driven Mobile GUI Testing0
AutoRad-Lung: A Radiomic-Guided Prompting Autoregressive Vision-Language Model for Lung Nodule Malignancy Prediction0
Autoregressive + Chain of Thought = Recurrent: Recurrence's Role in Language Models' Computability and a Revisit of Recurrent Transformer0
Autoregressive Language Model for Zero-shot Constrained Keyphrase Generation0
Autoregressive Language Models for Knowledge Base Population: A case study in the space mission domain0
Autoregressive Large Language Models are Computationally Universal0
Autoregressive Linguistic Steganography Based on BERT and Consistency Coding0
Limitations of Autoregressive Models and Their Alternatives0
Autoregressive Speech Synthesis with Next-Distribution Prediction0
Autoregressive Speech Synthesis without Vector Quantization0
Auto-Sizing Neural Networks: With Applications to n-gram Language Models0
AutoTask: Task Aware Multi-Faceted Single Model for Multi-Task Ads Relevance0
Auto-TA: Towards Scalable Automated Thematic Analysis (TA) via Multi-Agent Large Language Models with Reinforcement Learning0
Autoware.Flex: Human-Instructed Dynamically Reconfigurable Autonomous Driving Systems0
A Vector-Based Approach to Few-Shot Veracity Classification for Automated Fact-Checking0
AviationGPT: A Large Language Model for the Aviation Domain0
AVIS: Autonomous Visual Information Seeking with Large Language Model Agent0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features0
A Vision-Language Model for Focal Liver Lesion Classification0
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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