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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 27512800 of 17610 papers

TitleStatusHype
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video UnderstandingCode1
Korean-Specific Dataset for Table Question AnsweringCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
An Open Source Data Contamination Report for Large Language ModelsCode1
Elastic Weight Removal for Faithful and Abstractive Dialogue GenerationCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
KnowMAN: Weakly Supervised Multinomial Adversarial NetworksCode1
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing DetectionCode1
Kosmos-2: Grounding Multimodal Large Language Models to the WorldCode1
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than GeneratorsCode1
ELI5: Long Form Question AnsweringCode1
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language ModelsCode1
CrAM: A Compression-Aware MinimizerCode1
CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web VideosCode1
Knowledge Rumination for Pre-trained Language ModelsCode1
BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingCode1
Knowledge Transfer from Pre-trained Language Models to Cif-based Speech Recognizers via Hierarchical DistillationCode1
Accurate Retraining-free Pruning for Pretrained Encoder-based Language ModelsCode1
Long-Short Transformer: Efficient Transformers for Language and VisionCode1
Knowledge Prompting in Pre-trained Language Model for Natural Language UnderstandingCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text GenerationCode1
Knowledge Perceived Multi-modal Pretraining in E-commerceCode1
Knowledge Unlearning for Mitigating Privacy Risks in Language ModelsCode1
K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATIONCode1
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model ProgramsCode1
ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign UsersCode1
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News ArticlesCode1
CPLLM: Clinical Prediction with Large Language ModelsCode1
ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced AdapterCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysisCode1
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model FinetuningCode1
LSBert: A Simple Framework for Lexical SimplificationCode1
EMMA: Efficient Visual Alignment in Multi-Modal LLMsCode1
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression RecognitionCode1
Fact-checking information from large language models can decrease headline discernmentCode1
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic DimensionCode1
CoVR-2: Automatic Data Construction for Composed Video RetrievalCode1
Character-level Chinese Backpack Language ModelsCode1
Emotion-Aware Transformer Encoder for Empathetic Dialogue GenerationCode1
Luna: Linear Unified Nested AttentionCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERTCode1
ReMeDi: Resources for Multi-domain, Multi-service, Medical DialoguesCode1
Knowledge Graph Generation From TextCode1
Annotation-Efficient Preference Optimization for Language Model AlignmentCode1
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from TextCode1
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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