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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1675116800 of 17610 papers

TitleStatusHype
A Role-specific Guided Large Language Model for Ophthalmic Consultation Based on Stylistic DifferentiationCode0
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model CompressionCode0
From Discrimination to Generation: Knowledge Graph Completion with Generative TransformerCode0
End-to-End Speech Recognition and Disfluency Removal with Acoustic Language Model PretrainingCode0
From Disfluency Detection to Intent Detection and Slot FillingCode0
Can Github issues be solved with Tree Of Thoughts?Code0
End-to-End Task-Oriented Dialog Modeling with Semi-Structured Knowledge ManagementCode0
From Distributional to Overton Pluralism: Investigating Large Language Model AlignmentCode0
A Robust Bias Mitigation Procedure Based on the Stereotype Content ModelCode0
From English to ASIC: Hardware Implementation with Large Language ModelCode0
From Form(s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense ConsistencyCode0
In-Context Learning through the Bayesian PrismCode0
ArNLI: Arabic Natural Language Inference for Entailment and Contradiction DetectionCode0
Energy-Based Reward Models for Robust Language Model AlignmentCode0
From Gaze to Insight: Bridging Human Visual Attention and Vision Language Model Explanation for Weakly-Supervised Medical Image SegmentationCode0
A Low-Resource Approach to the Grammatical Error Correction of UkrainianCode0
A Feasible Framework for Arbitrary-Shaped Scene Text RecognitionCode0
Heterogeneous Subgraph Transformer for Fake News DetectionCode0
Integrated Semantic and Phonetic Post-correction for Chinese Speech RecognitionCode0
Can Generative LLMs Create Query Variants for Test Collections? An Exploratory StudyCode0
Are VLMs Really BlindCode0
Are Some Words Worth More than Others?Code0
From Interests to Insights: An LLM Approach to Course Recommendations Using Natural Language QueriesCode0
A Recurrent BERT-based Model for Question GenerationCode0
Can discrete information extraction prompts generalize across language models?Code0
Integrating A.I. in Higher Education: Protocol for a Pilot Study with 'SAMCares: An Adaptive Learning Hub'Code0
DALLMi: Domain Adaption for LLM-based Multi-label ClassifierCode0
A Reality Check on Context Utilisation for Retrieval-Augmented GenerationCode0
Adversarial Style Augmentation via Large Language Model for Robust Fake News DetectionCode0
Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text GenerationCode0
AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identificationCode0
From Machine Translation to Code-Switching: Generating High-Quality Code-Switched TextCode0
Is GPT-3 a Good Data Annotator?Code0
From Markov to Laplace: How Mamba In-Context Learns Markov ChainsCode0
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language UnderstandingCode0
Adversarially Regularising Neural NLI Models to Integrate Logical Background KnowledgeCode0
From MTEB to MTOB: Retrieval-Augmented Classification for Descriptive GrammarsCode0
Improved Differentiable Architecture Search for Language Modeling and Named Entity RecognitionCode0
From Natural Language to Simulations: Applying GPT-3 Codex to Automate Simulation Modeling of Logistics SystemsCode0
From neighborhood to parenthood: the advantages of dependency representation over bigrams in Brown clusteringCode0
ALoFTRAG: Automatic Local Fine Tuning for Retrieval Augmented GenerationCode0
Is Supervised Syntactic Parsing Beneficial for Language Understanding? An Empirical InvestigationCode0
Adversarial Dropout for Recurrent Neural NetworksCode0
Accommodating Audio Modality in CLIP for Multimodal ProcessingCode0
From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMsCode0
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate ModelsCode0
Cynical Selection of Language Model Training DataCode0
1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position SelectorCode0
Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair PredictionCode0
Hierarchical Character Embeddings: Learning Phonological and Semantic Representations in Languages of Logographic Origin using Recursive Neural NetworksCode0
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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