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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 24012450 of 17610 papers

TitleStatusHype
Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action DetectionCode1
A Pilot Study of Text-to-SQL Semantic Parsing for VietnameseCode1
A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capabilityCode1
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
A Pilot Study for BERT Language Modelling and Morphological Analysis for Ancient and Medieval GreekCode1
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMsCode1
A Generative Language Model for Few-shot Aspect-Based Sentiment AnalysisCode1
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language ModelingCode1
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model BiasCode1
CDLM: Cross-Document Language ModelingCode1
Cross-Align: Modeling Deep Cross-lingual Interactions for Word AlignmentCode1
Masked Structural Growth for 2x Faster Language Model Pre-trainingCode1
Interpretable Language Modeling via Induction-head Ngram ModelsCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
A Generative Approach for Script Event Prediction via Contrastive Fine-tuningCode1
Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language ModelCode1
CriticEval: Evaluating Large Language Model as CriticCode1
Instruction-Driven Game Engines on Large Language ModelsCode1
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
APB: Accelerating Distributed Long-Context Inference by Passing Compressed Context Blocks across GPUsCode1
A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language ProcessingCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
2SSP: A Two-Stage Framework for Structured Pruning of LLMsCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofingCode1
Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility PredictionCode1
CrAM: A Compression-Aware MinimizerCode1
InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction OperatorsCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
Injecting Numerical Reasoning Skills into Language ModelsCode1
InstructDET: Diversifying Referring Object Detection with Generalized InstructionsCode1
CoVR-2: Automatic Data Construction for Composed Video RetrievalCode1
-former: Infinite Memory TransformerCode1
RealFormer: Transformer Likes Residual AttentionCode1
InforMask: Unsupervised Informative Masking for Language Model PretrainingCode1
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-TrainingCode1
-former: Infinite Memory TransformerCode1
Counterfactual Token Generation in Large Language ModelsCode1
CPT: Efficient Deep Neural Network Training via Cyclic PrecisionCode1
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from TextCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
A Generalizable Approach to Learning OptimizersCode1
CPLLM: Clinical Prediction with Large Language ModelsCode1
InfoLM: A New Metric to Evaluate Summarization & Data2Text GenerationCode1
InstructEdit: Improving Automatic Masks for Diffusion-based Image Editing With User InstructionsCode1
Bring Your Own Data! Self-Supervised Evaluation for Large Language ModelsCode1
INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval 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