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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 30513100 of 17610 papers

TitleStatusHype
Free and Customizable Code Documentation with LLMs: A Fine-Tuning ApproachCode1
C-LLM: Learn to Check Chinese Spelling Errors Character by CharacterCode1
FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language ModelsCode1
Frequency Explains the Inverse Correlation of Large Language Models' Size, Training Data Amount, and Surprisal's Fit to Reading TimesCode1
Bioformer: an efficient transformer language model for biomedical text miningCode1
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context LearningCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
Optimization-based Prompt Injection Attack to LLM-as-a-JudgeCode1
Large Language Models are not Fair EvaluatorsCode1
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
BioBERT: a pre-trained biomedical language representation model for biomedical text miningCode1
Clover: Towards A Unified Video-Language Alignment and Fusion ModelCode1
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language ModelingCode1
BioBART: Pretraining and Evaluation of A Biomedical Generative Language ModelCode1
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain ModelingCode1
Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking ModelsCode1
Six Dragons Fly Again: Reviving 15th-Century Korean Court Music with Transformers and Novel EncodingCode1
CDLM: Cross-Document Language ModelingCode1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Large Language Models are Pretty Good Zero-Shot Video Game Bug DetectorsCode1
Personalized Autonomous Driving with Large Language Models: Field ExperimentsCode1
Large-Scale Contextualised Language Modelling for NorwegianCode1
Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!Code1
Critic-Guided Decoding for Controlled Text GenerationCode1
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment RecommendationCode1
Large Language Model (LLM) as a System of Multiple Expert Agents: An Approach to solve the Abstraction and Reasoning Corpus (ARC) ChallengeCode1
Large Language Model-Powered Smart Contract Vulnerability Detection: New PerspectivesCode1
FuseCap: Leveraging Large Language Models for Enriched Fused Image CaptionsCode1
Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language ModelCode1
Cross-Align: Modeling Deep Cross-lingual Interactions for Word AlignmentCode1
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk PredictionCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
ClusterLLM: Large Language Models as a Guide for Text ClusteringCode1
A Study of Generative Large Language Model for Medical Research and HealthcareCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
CriticEval: Evaluating Large Language Model as CriticCode1
Large Language Model as a Policy Teacher for Training Reinforcement Learning AgentsCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Large Language Model for Multi-objective Evolutionary OptimizationCode1
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language ModelsCode1
CrAM: A Compression-Aware MinimizerCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic ActivitiesCode1
GateLoop: Fully Data-Controlled Linear Recurrence for Sequence ModelingCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed Human AttentionCode1
GenAug: Data Augmentation for Finetuning Text GeneratorsCode1
Gemstones: A Model Suite for Multi-Faceted Scaling LawsCode1
Large Language Model Inference Acceleration: A Comprehensive Hardware PerspectiveCode1
CPLLM: Clinical Prediction with 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