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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 6451–6500 of 17610 papers

TitleStatusHype
Computational Bottlenecks of Training Small-scale Large Language Models—0
FedBaF: Federated Learning Aggregation Biased by a Foundation Model—0
Bielik 7B v0.1: A Polish Language Model -- Development, Insights, and Evaluation—0
A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs—0
AlignCap: Aligning Speech Emotion Captioning to Human Preferences—0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms—0
Zero-shot Object Navigation with Vision-Language Models Reasoning—0
Unbounded: A Generative Infinite Game of Character Life Simulation—0
Provably Robust Watermarks for Open-Source Language Models—0
Structure Language Models for Protein Conformation Generation—0
Taipan: Efficient and Expressive State Space Language Models with Selective Attention—0
LMLPA: Language Model Linguistic Personality Assessment—0
LEGO: Language Model Building Blocks—0
Lightweight Neural App Control—0
MojoBench: Language Modeling and Benchmarks for Mojo—0
CoreInfer: Accelerating Large Language Model Inference with Semantics-Inspired Adaptive Sparse Activation—0
Generalizations across filler-gap dependencies in neural language modelsCode0
Future Token Prediction -- Causal Language Modelling with Per-Token Semantic State Vector for Multi-Token Prediction—0
DIRI: Adversarial Patient Reidentification with Large Language Models for Evaluating Clinical Text Anonymization—0
Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language ModelingCode0
Chatting with Bots: AI, Speech Acts, and the Edge of Assertion—0
Continuous Speech Tokenizer in Text To SpeechCode0
GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks—0
Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model AgentCode0
Improving Pinterest Search Relevance Using Large Language Models—0
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR—0
Exploring Forgetting in Large Language Model Pre-Training—0
DNAHLM -- DNA sequence and Human Language mixed large language ModelCode0
MeMDLM: De Novo Membrane Protein Design with Masked Discrete Diffusion Protein Language Models—0
Remote Timing Attacks on Efficient Language Model Inference—0
Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generation—0
Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language ModelsCode0
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment—0
SaVe-TAG: Semantic-aware Vicinal Risk Minimization for Long-Tailed Text-Attributed Graphs—0
Science Out of Its Ivory Tower: Improving Accessibility with Reinforcement LearningCode0
Self-calibration for Language Model Quantization and Pruning—0
Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User ModelingCode0
PLDR-LLM: Large Language Model from Power Law Decoder RepresentationsCode0
To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning—0
KatzBot: Revolutionizing Academic Chatbot for Enhanced CommunicationCode0
Language Models are Symbolic Learners in Arithmetic—0
Neural Search Space in Gboard Decoder—0
LSCodec: Low-Bitrate and Speaker-Decoupled Discrete Speech Codec—0
Tokenization as Finite-State Transduction—0
No more hard prompts: SoftSRV prompting for synthetic data generation—0
Large Body Language Models—0
Opportunities and Challenges of Generative-AI in Finance—0
The effect of fine-tuning on language model toxicityCode0
Subword Embedding from Bytes Gains Privacy without Sacrificing Accuracy and Complexity—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified