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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1545115500 of 17610 papers

TitleStatusHype
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Language Model Transformers as Evaluators for Open-domain DialoguesCode0
Language Model Training Paradigms for Clinical Feature EmbeddingsCode0
PeriGuru: A Peripheral Robotic Mobile App Operation Assistant based on GUI Image Understanding and Prompting with LLMCode0
LittleMu: Deploying an Online Virtual Teaching Assistant via Heterogeneous Sources Integration and Chain of Teach PromptsCode0
Self-Evaluation of Large Language Model based on Glass-box FeaturesCode0
Self-Evolution Learning for Discriminative Language Model PretrainingCode0
Supervised Contextual Embeddings for Transfer Learning in Natural Language Processing TasksCode0
Enhanced Language Model Truthfulness with Learnable Intervention and Uncertainty ExpressionCode0
Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion EnhancementCode0
Downstream Trade-offs of a Family of Text WatermarksCode0
Penny-Wise and Pound-Foolish in Deepfake DetectionCode0
PEACH: Pre-Training Sequence-to-Sequence Multilingual Models for Translation with Semi-Supervised Pseudo-Parallel Document GenerationCode0
Selfie: Self-supervised Pretraining for Image EmbeddingCode0
Learning Recurrent Binary/Ternary WeightsCode0
LitLinker: Supporting the Ideation of Interdisciplinary Contexts with Large Language Models for Teaching Literature in Elementary SchoolsCode0
Language Model Tokenizers Introduce Unfairness Between LanguagesCode0
Language Models with Pre-Trained (GloVe) Word EmbeddingsCode0
A general language model for peptide identificationCode0
Learning Python Code Suggestion with a Sparse Pointer NetworkCode0
The merits of Universal Language Model Fine-tuning for Small Datasets -- a case with Dutch book reviewsCode0
Towards Community-Driven Agents for Machine Learning EngineeringCode0
KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney DiseaseCode0
PclGPT: A Large Language Model for Patronizing and Condescending Language DetectionCode0
Paying More Attention to Source Context: Mitigating Unfaithful Translations from Large Language ModelCode0
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classificationCode0
Pay Attention when RequiredCode0
PAYADOR: A Minimalist Approach to Grounding Language Models on Structured Data for Interactive Storytelling and Role-playing GamesCode0
KidLM: Advancing Language Models for Children -- Early Insights and Future DirectionsCode0
Patterns versus Characters in Subword-aware Neural Language ModelingCode0
Demystifying Instruction Mixing for Fine-tuning Large Language ModelsCode0
Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in RoboticsCode0
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language ModelCode0
PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation ModelCode0
Surgical Feature-Space Decomposition of LLMs: Why, When and How?Code0
The MiniPile Challenge for Data-Efficient Language ModelsCode0
Multi-Grained Patch Training for Efficient LLM-based RecommendationCode0
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text GuidanceCode0
Self-Supervised Contrastive Learning with Adversarial Perturbations for Defending Word Substitution-based AttacksCode0
LAMP: A Language Model on the MapCode0
Self-Supervised Knowledge Assimilation for Expert-Layman Text Style TransferCode0
Training Neural Networks as Recognizers of Formal LanguagesCode0
PatchProt: Hydrophobic patch prediction using protein foundation modelsCode0
Partially Shuffling the Training Data to Improve Language ModelsCode0
Training Neural Response Selection for Task-Oriented Dialogue SystemsCode0
Parsing as Language ModelingCode0
Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language ModelsCode0
Self-supervised Preference Optimization: Enhance Your Language Model with Preference Degree AwarenessCode0
The Mysterious Case of Neuron 1512: Injectable Realignment Architectures Reveal Internal Characteristics of Meta's Llama 2 ModelCode0
Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: The Example of Cognitive ControlCode0
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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