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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 23512400 of 17610 papers

TitleStatusHype
Facilitating large language model Russian adaptation with Learned Embedding PropagationCode1
ExpertQA: Expert-Curated Questions and Attributed AnswersCode1
Explaining Answers with Entailment TreesCode1
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question AnsweringCode1
Explaining Datasets in Words: Statistical Models with Natural Language ParametersCode1
ExaRanker: Explanation-Augmented Neural RankerCode1
Evolving Deep Neural NetworksCode1
Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model CommunicationCode1
Agentic Skill DiscoveryCode1
Evolutionary Large Language Model for Automated Feature TransformationCode1
Excuse me, sir? Your language model is leaking (information)Code1
Exploiting BERT For Multimodal Target Sentiment Classification Through Input Space TranslationCode1
Event Causality Identification via Derivative Prompt Joint LearningCode1
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM FamilyCode1
Evaluation of large language models for discovery of gene set functionCode1
Emergent Representations of Program Semantics in Language Models Trained on ProgramsCode1
Supervised Learning and Large Language Model Benchmarks on Mental Health Datasets: Cognitive Distortions and Suicidal Risks in Chinese Social MediaCode1
Evaluating Retrieval Quality in Retrieval-Augmented GenerationCode1
Evaluating the Robustness of Retrieval Pipelines with Query Variation GeneratorsCode1
Evaluating Morphological Alignment of Tokenizers in 70 LanguagesCode1
Evaluation Benchmarks for Spanish Sentence RepresentationsCode1
e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language TasksCode1
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language InferenceCode1
Factorization tricks for LSTM networksCode1
Evaluating Human-Language Model InteractionCode1
Evaluating Language Model Context Windows: A "Working Memory" Test and Inference-time CorrectionCode1
EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability TreesCode1
InferCept: Efficient Intercept Support for Augmented Large Language Model InferenceCode1
Evaluating Attribution in Dialogue Systems: The BEGIN BenchmarkCode1
Evaluating Language Model Finetuning Techniques for Low-resource LanguagesCode1
ApiQ: Finetuning of 2-Bit Quantized Large Language ModelCode1
Euphemistic Phrase Detection by Masked Language ModelCode1
Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model EvaluationCode1
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial OptimizationCode1
Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language ModelCode1
EvalCrafter: Benchmarking and Evaluating Large Video Generation ModelsCode1
Mathfish: Evaluating Language Model Math Reasoning via Grounding in Educational CurriculaCode1
A Pilot Study of Text-to-SQL Semantic Parsing for VietnameseCode1
A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capabilityCode1
Espresso: A Fast End-to-end Neural Speech Recognition ToolkitCode1
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
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence GenerationCode1
Escalation Risks from Language Models in Military and Diplomatic Decision-MakingCode1
EscapeBench: Pushing Language Models to Think Outside the BoxCode1
Masked Structural Growth for 2x Faster Language Model Pre-trainingCode1
ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market DomainCode1
Establishing baselines for generative discovery of inorganic crystalsCode1
Evaluating Language Models as Synthetic Data GeneratorsCode1
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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