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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 99019950 of 17610 papers

TitleStatusHype
Evaluating ChatGPT as a Question Answering System: A Comprehensive Analysis and Comparison with Existing Models0
GTA: Gated Toxicity Avoidance for LM Performance PreservationCode0
Audio-Visual LLM for Video Understanding0
Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Need0
Linguistic and Structural Basis of Engineering Design Knowledge0
Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning0
Stateful Large Language Model Serving with Pensieve0
Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorization Risks In Language ModelsCode0
Teamwork Dimensions Classification Using BERT0
TCNCA: Temporal Convolution Network with Chunked Attention for Scalable Sequence Processing0
Language-assisted Vision Model Debugger: A Sample-Free Approach to Finding and Fixing Bugs0
PerfRL: A Small Language Model Framework for Efficient Code Optimization0
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing0
Enhancing Medical Specialty Assignment to Patients using NLP Techniques0
Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the EdgeCode0
Domain Adaptation of a State of the Art Text-to-SQL Model: Lessons Learned and Challenges Found0
Image and Data Mining in Reticular Chemistry Using GPT-4V0
Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class ClassificationCode0
INSPECT: Intrinsic and Systematic Probing Evaluation for Code TransformersCode0
Illicit Darkweb Classification via Natural-language Processing: Classifying Illicit Content of Webpages based on Textual Information0
How to Determine the Most Powerful Pre-trained Language Model without Brute Force Fine-tuning? An Empirical SurveyCode0
User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning0
Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generation0
Localized Symbolic Knowledge Distillation for Visual Commonsense ModelsCode0
Ophtha-LLaMA2: A Large Language Model for Ophthalmology0
Retrieval-based Video Language Model for Efficient Long Video Question Answering0
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation0
Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models0
Language Model Knowledge Distillation for Efficient Question Answering in SpanishCode0
Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsCode0
Improved Visual Grounding through Self-Consistent Explanations0
ConVRT: Consistent Video Restoration Through Turbulence with Test-time Optimization of Neural Video Representations0
Comparing Large Language Model AI and Human-Generated Coaching Messages for Behavioral Weight Loss0
Combining inherent knowledge of vision-language models with unsupervised domain adaptation through strong-weak guidanceCode0
A Block Metropolis-Hastings Sampler for Controllable Energy-based Text Generation0
Chain of Code: Reasoning with a Language Model-Augmented Code EmulatorCode0
Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies0
Efficient End-to-end Language Model Fine-tuning on Graphs0
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
Using a Large Language Model to generate a Design Structure Matrix0
Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models0
Language Model Alignment with Elastic ResetCode0
Teaching Specific Scientific Knowledge into Large Language Models through Additional TrainingCode0
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning0
LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent EcosystemCode0
Run LoRA Run: Faster and Lighter LoRA Implementations0
Sig-Networks Toolkit: Signature Networks for Longitudinal Language ModellingCode0
FoMo Rewards: Can we cast foundation models as reward functions?0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition0
Empowering ChatGPT-Like Large-Scale Language Models with Local Knowledge Base for Industrial Prognostics and Health Management0
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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