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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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
FedJudge: Federated Legal Large Language ModelCode1
Epidemic Modeling with Generative AgentsCode1
Entropy-Regularized Token-Level Policy Optimization for Language Agent ReinforcementCode1
IoT-LM: Large Multisensory Language Models for the Internet of ThingsCode1
ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and GenerationCode1
The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification TasksCode1
Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3Code1
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model RecommendationCode1
Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language ModelsCode1
Entity-aware Transformers for Entity SearchCode1
Enriching Music Descriptions with a Finetuned-LLM and Metadata for Text-to-Music RetrievalCode1
Iterative Few-shot Semantic Segmentation from Image Label TextCode1
It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story BooksCode1
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language ModelsCode1
Entity Tracking in Language ModelsCode1
Enhancing RL Safety with Counterfactual LLM ReasoningCode1
Enhancing Reasoning to Adapt Large Language Models for Domain-Specific ApplicationsCode1
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment GenerationCode1
A Comparison of Methods for OOV-word Recognition on a New Public DatasetCode1
Enhancing Perception of Key Changes in Remote Sensing Image Change CaptioningCode1
JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue DatasetCode1
JobBERT: Understanding Job Titles through SkillsCode1
Enhancing Vision-Language Model with Unmasked Token AlignmentCode1
RetGen: A Joint framework for Retrieval and Grounded Text Generation ModelingCode1
XMoE: Sparse Models with Fine-grained and Adaptive Expert SelectionCode1
Enhancing Domain Adaptation through Prompt Gradient AlignmentCode1
ARS: Automatic Routing Solver with Large Language ModelsCode1
KALA: Knowledge-Augmented Language Model AdaptationCode1
Enhancing Indic Handwritten Text Recognition Using Global Semantic InformationCode1
Coherence boosting: When your pretrained language model is not paying enough attentionCode1
Enhancing Dialogue Generation via Dynamic Graph Knowledge AggregationCode1
ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced AdapterCode1
Large Language Models are Learnable Planners for Long-Term RecommendationCode1
Enhancing Chinese Pre-trained Language Model via Heterogeneous Linguistics GraphCode1
Kformer: Knowledge Injection in Transformer Feed-Forward LayersCode1
Boosted Prompt Ensembles for Large Language ModelsCode1
KinyaBERT: a Morphology-aware Kinyarwanda Language ModelCode1
KITLM: Domain-Specific Knowledge InTegration into Language Models for Question AnsweringCode1
Enhancing Clinical BERT Embedding using a Biomedical Knowledge BaseCode1
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic DimensionCode1
UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language ModelCode1
Character-level Chinese Backpack Language ModelsCode1
Content-Based Collaborative Generation for Recommender SystemsCode1
Enhancing Multilingual Language Model with Massive Multilingual Knowledge TriplesCode1
Enhancing Biomedical Relation Extraction with DirectionalityCode1
Enhancing Conversational Search: Large Language Model-Aided Informative Query RewritingCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question AnsweringCode1
ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from TransformerCode1
Enhancing Multi-modal and Multi-hop Question Answering via Structured Knowledge and Unified Retrieval-GenerationCode1
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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