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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 60516100 of 17610 papers

TitleStatusHype
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model0
Vocabulary Attack to Hijack Large Language Model Applications0
Mai Ho'omāuna i ka 'Ai: Language Models Improve Automatic Speech Recognition in Hawaiian0
FPT: Feature Prompt Tuning for Few-shot Readability AssessmentCode0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison0
From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives0
Estimating the Causal Effects of Natural Logic Features in Transformer-Based NLI Models0
Improving Topic Relevance Model by Mix-structured Summarization and LLM-based Data Augmentation0
Enhancing Human-Computer Interaction in Chest X-ray Analysis using Vision and Language Model with Eye Gaze Patterns0
Calibrating the Confidence of Large Language Models by Eliciting Fidelity0
Testing the Effect of Code Documentation on Large Language Model Code Understanding0
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in ConversationCode0
ANGOFA: Leveraging OFA Embedding Initialization and Synthetic Data for Angolan Language ModelCode0
Manipulating and Mitigating Generative Model Biases without Retraining0
PhonologyBench: Evaluating Phonological Skills of Large Language Models0
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale PredictionCode9
I-Design: Personalized LLM Interior Designer0
Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs0
Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and OptimizationCode1
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource LanguagesCode0
Language Model Guided Interpretable Video Action ReasoningCode0
Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized ContextsCode0
M2SA: Multimodal and Multilingual Model for Sentiment Analysis of TweetsCode0
Asymptotics of Language Model Alignment0
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language ModelsCode0
Sentence-level Media Bias Analysis with Event Relation GraphCode0
Octopus: On-device language model for function calling of software APIs0
Octopus v2: On-device language model for super agent0
IndoCulture: Exploring Geographically-Influenced Cultural Commonsense Reasoning Across Eleven Indonesian Provinces0
MotionChain: Conversational Motion Controllers via Multimodal PromptsCode2
Automated User Story Generation with Test Case Specification Using Large Language Model0
A Survey on Large Language Model-Based Game AgentsCode4
Topic-Based Watermarks for Large Language Models0
mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning0
Laying Anchors: Semantically Priming Numerals in Language ModelingCode0
Effective internal language model training and fusion for factorized transducer model0
Large Language Models for Orchestrating Bimanual RobotsCode1
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal DomainCode1
Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments0
Stream of Search (SoS): Learning to Search in LanguageCode2
Stable Code Technical Report0
AISPACE at SemEval-2024 task 8: A Class-balanced Soft-voting System for Detecting Multi-generator Machine-generated Text0
Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training0
ARAGOG: Advanced RAG Output GradingCode2
Effectively Prompting Small-sized Language Models for Cross-lingual Tasks via Winning Tickets0
Do language models plan ahead for future tokens?Code0
The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis0
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?Code0
TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model0
LITE: Modeling Environmental Ecosystems with Multimodal Large Language ModelsCode1
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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