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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1650116550 of 17610 papers

TitleStatusHype
Diagnosing our datasets: How does my language model learn clinical information?Code0
Improving Variational Autoencoder for Text Modelling with Timestep-Wise RegularisationCode0
Improving Variational Autoencoders with Density Gap-based RegularizationCode0
Dispersed Exponential Family Mixture VAEs for Interpretable Text GenerationCode0
ChamaleonLLM: Batch-Aware Dynamic Low-Rank Adaptation via Inference-Time ClustersCode0
Device Placement Optimization with Reinforcement LearningCode0
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?Code0
Challenges in Measuring Bias via Open-Ended Language GenerationCode0
Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution PipelineCode0
Assertion Detection Large Language Model In-context Learning LoRA Fine-tuningCode0
Efficient Inference for Large Language Model-based Generative RecommendationCode0
AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated TextCode0
Chain-of-Model Learning for Language ModelCode0
Chain of Code: Reasoning with a Language Model-Augmented Code EmulatorCode0
Agentic Society: Merging skeleton from real world and texture from Large Language ModelCode0
Efficient Language Model Training through Cross-Lingual and Progressive Transfer LearningCode0
Chaining thoughts and LLMs to learn DNA structural biophysicsCode0
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language ModelsCode0
Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LMCode0
AMONGAGENTS: Evaluating Large Language Models in the Interactive Text-Based Social Deduction GameCode0
Assay2Mol: large language model-based drug design using BioAssay contextCode0
HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination EvaluationCode0
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model TrainingCode0
Detection of depression on social networks using transformers and ensemblesCode0
CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language GenerationsCode0
CEval: A Benchmark for Evaluating Counterfactual Text GenerationCode0
FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model CompressionCode0
Image-guided topic modeling for interpretable privacy classificationCode0
Detection of circular permutations by Protein Language ModelsCode0
Handling Massive N-Gram Datasets EfficientlyCode0
FlauBERT : des mod\`eles de langue contextualis\'es pr\'e-entra\^ \'es pour le fran (FlauBERT : Unsupervised Language Model Pre-training for French)Code0
Detection-Fusion for Knowledge Graph Extraction from VideosCode0
FlauBERT: Unsupervised Language Model Pre-training for FrenchCode0
Detecting the Clinical Features of Difficult-to-Treat Depression using Synthetic Data from Large Language ModelsCode0
Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language ModelsCode0
Centurio: On Drivers of Multilingual Ability of Large Vision-Language ModelCode0
AMOM: Adaptive Masking over Masking for Conditional Masked Language ModelCode0
Efficient Machine Translation Domain AdaptationCode0
Handwritten Code Recognition for Pen-and-Paper CS EducationCode0
Aspects of human memory and Large Language ModelsCode0
Efficient Medical Question Answering with Knowledge-Augmented Question GenerationCode0
Agentic Reasoning: Reasoning LLMs with Tools for the Deep ResearchCode0
Detecting Polarized Topics Using Partisanship-aware Contextualized Topic EmbeddingsCode0
Detecting out-of-distribution text using topological features of transformer-based language modelsCode0
HanTrans: An Empirical Study on Cross-Era Transferability of Chinese Pre-trained Language ModelCode0
Image Safeguarding: Reasoning with Conditional Vision Language Model and Obfuscating Unsafe Content CounterfactuallyCode0
Detecting Non-literal Translations by Fine-tuning Cross-lingual Pre-trained Language ModelsCode0
Detecting Errors through Ensembling Prompts (DEEP): An End-to-End LLM Framework for Detecting Factual ErrorsCode0
Centered Masking for Language-Image Pre-TrainingCode0
CellTypeAgent: Trustworthy cell type annotation with Large Language ModelsCode0
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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