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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 25012550 of 17610 papers

TitleStatusHype
Certifying LLM Safety against Adversarial PromptingCode1
DeViL: Decoding Vision features into LanguageCode1
Are Emergent Abilities in Large Language Models just In-Context Learning?Code1
LinkTransformer: A Unified Package for Record Linkage with Transformer Language ModelsCode1
Let the Models Respond: Interpreting Language Model Detoxification Through the Lens of Prompt DependenceCode1
Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical NotesCode1
Image Hijacks: Adversarial Images can Control Generative Models at RuntimeCode1
Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language ModelCode1
RepCodec: A Speech Representation Codec for Speech TokenizationCode1
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties PredictionCode1
Improving antibody language models with native pairingCode1
A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERCode1
CoVR-2: Automatic Data Construction for Composed Video RetrievalCode1
PeptideBERT: A Language Model based on Transformers for Peptide Property PredictionCode1
TextrolSpeech: A Text Style Control Speech Corpus With Codec Language Text-to-Speech ModelsCode1
Detecting Language Model Attacks with PerplexityCode1
ZC3: Zero-Shot Cross-Language Code Clone DetectionCode1
ORES: Open-vocabulary Responsible Visual SynthesisCode1
SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific ResearchCode1
Prompting Visual-Language Models for Dynamic Facial Expression RecognitionCode1
VIGC: Visual Instruction Generation and CorrectionCode1
CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model BiasCode1
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-FinetuningCode1
Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language ModelsCode1
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in RecommendationCode1
Multi-event Video-Text RetrievalCode1
ROSGPT_Vision: Commanding Robots Using Only Language Models' PromptsCode1
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User SimulatorCode1
Fact-checking information from large language models can decrease headline discernmentCode1
SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit DifferentiationCode1
Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code GenerationCode1
Steering Language Models With Activation EngineeringCode1
ChatEDA: A Large Language Model Powered Autonomous Agent for EDACode1
Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural languageCode1
Chinese Spelling Correction as Rephrasing Language ModelCode1
End-to-End Beam Retrieval for Multi-Hop Question AnsweringCode1
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time SeriesCode1
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme DetectionCode1
CMD: a framework for Context-aware Model self-DetoxificationCode1
PEvoLM: Protein Sequence Evolutionary Information Language ModelCode1
Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module OperationCode1
A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text SupervisionCode1
CausalLM is not optimal for in-context learningCode1
LLM Self Defense: By Self Examination, LLMs Know They Are Being TrickedCode1
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and TextCode1
Pairing interacting protein sequences using masked language modelingCode1
ZYN: Zero-Shot Reward Models with Yes-No Questions for RLAIFCode1
Self-Alignment with Instruction BacktranslationCode1
Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-ModelingCode1
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search EngineCode1
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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