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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 35513600 of 17610 papers

TitleStatusHype
LM-Critic: Language Models for Unsupervised Grammatical Error CorrectionCode1
ContraCLM: Contrastive Learning For Causal Language ModelCode1
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer LearningCode1
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense GenerationCode1
Contrastive Chain-of-Thought PromptingCode1
KITLM: Domain-Specific Knowledge InTegration into Language Models for Question AnsweringCode1
LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot DetectionCode1
LMentry: A Language Model Benchmark of Elementary Language TasksCode1
LLMVA-GEBC: Large Language Model with Video Adapter for Generic Event Boundary CaptioningCode1
Data Efficient Masked Language Modeling for Vision and LanguageCode1
LLMZip: Lossless Text Compression using Large Language ModelsCode1
Stealthy Attack on Large Language Model based RecommendationCode1
LML-DAP: Language Model Learning a Dataset for Data-Augmented PredictionCode1
Data Augmentation using Pre-trained Transformer ModelsCode1
Contrastive Learning for Prompt-Based Few-Shot Language LearnersCode1
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text ClassificationCode1
LLM Self Defense: By Self Examination, LLMs Know They Are Being TrickedCode1
DARTS: Differentiable Architecture SearchCode1
Enhancing Multilingual Language Model with Massive Multilingual Knowledge TriplesCode1
Contrastive Learning with Hard Negative Entities for Entity Set ExpansionCode1
DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNACode1
Knowledge Distillation for BERT Unsupervised Domain AdaptationCode1
LLMs Can Simulate Standardized Patients via Agent CoevolutionCode1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documentsCode1
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based RepresentationsCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
Knowledge Enhanced Masked Language Model for Stance DetectionCode1
DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference AccelerationCode1
Picard understanding Darmok: A Dataset and Model for Metaphor-Rich Translation in a Constructed LanguageCode1
Controllable Generation from Pre-trained Language Models via Inverse PromptingCode1
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model EvaluationCode1
LLMSTEP: LLM proofstep suggestions in LeanCode1
DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance ScalingCode1
A Neural Algorithm of Artistic StyleCode1
Knowledge Prompting in Pre-trained Language Model for Natural Language UnderstandingCode1
DALE: Generative Data Augmentation for Low-Resource Legal NLPCode1
Knowledge Rumination for Pre-trained Language ModelsCode1
Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across ModalitiesCode1
Controllable Text Generation with Neurally-Decomposed OracleCode1
LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT PluginsCode1
KnowMAN: Weakly Supervised Multinomial Adversarial NetworksCode1
CXR-LLAVA: a multimodal large language model for interpreting chest X-ray imagesCode1
CycleFormer : TSP Solver Based on Language ModelingCode1
Controlled Text Generation as Continuous Optimization with Multiple ConstraintsCode1
Kosmos-2: Grounding Multimodal Large Language Models to the WorldCode1
Controlled Text Generation for Large Language Model with Dynamic Attribute GraphsCode1
K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATIONCode1
LLM-in-the-loop: Leveraging Large Language Model for Thematic AnalysisCode1
LLM-Neo: Parameter Efficient Knowledge Distillation for 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