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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7651–7700 of 17610 papers

TitleStatusHype
Domain Adaptation of a State of the Art Text-to-SQL Model: Lessons Learned and Challenges Found—0
Image and Data Mining in Reticular Chemistry Using GPT-4V—0
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing—0
PerfRL: A Small Language Model Framework for Efficient Code Optimization—0
Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the EdgeCode0
Language-assisted Vision Model Debugger: A Sample-Free Approach to Finding and Fixing Bugs—0
TypeFly: Flying Drones with Large Language ModelCode1
Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generation—0
User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning—0
Illicit Darkweb Classification via Natural-language Processing: Classifying Illicit Content of Webpages based on Textual Information—0
How to Determine the Most Powerful Pre-trained Language Model without Brute Force Fine-tuning? An Empirical SurveyCode0
Ophtha-LLaMA2: A Large Language Model for Ophthalmology—0
INSPECT: Intrinsic and Systematic Probing Evaluation for Code TransformersCode0
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation—0
SparQ Attention: Bandwidth-Efficient LLM InferenceCode1
Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class ClassificationCode0
Retrieval-based Video Language Model for Efficient Long Video Question Answering—0
DeltaZip: Efficient Serving of Multiple Full-Model-Tuned LLMsCode1
Fine-Tuning InstructPix2Pix for Advanced Image ColorizationCode1
Localized Symbolic Knowledge Distillation for Visual Commonsense ModelsCode0
Llama Guard: LLM-based Input-Output Safeguard for Human-AI ConversationsCode0
Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models—0
ConVRT: Consistent Video Restoration Through Turbulence with Test-time Optimization of Neural Video Representations—0
Language Model Knowledge Distillation for Efficient Question Answering in SpanishCode0
Improved Visual Grounding through Self-Consistent Explanations—0
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model ProgramsCode1
Comparing Large Language Model AI and Human-Generated Coaching Messages for Behavioral Weight Loss—0
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 Generation—0
Using a Large Language Model to generate a Design Structure Matrix—0
PartDistill: 3D Shape Part Segmentation by Vision-Language Model DistillationCode1
Auto-Vocabulary Semantic SegmentationCode1
Chain of Code: Reasoning with a Language Model-Augmented Code EmulatorCode0
Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies—0
On the Learnability of Watermarks for Language ModelsCode1
Efficient End-to-end Language Model Fine-tuning on Graphs—0
Empowering ChatGPT-Like Large-Scale Language Models with Local Knowledge Base for Industrial Prognostics and Health Management—0
Language Model Alignment with Elastic ResetCode0
LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent EcosystemCode0
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning—0
FoMo Rewards: Can we cast foundation models as reward functions?—0
Sig-Networks Toolkit: Signature Networks for Longitudinal Language ModellingCode0
Corporate Bankruptcy Prediction with Domain-Adapted BERT—0
VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic NavigationCode2
Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models—0
Compressed Context Memory For Online Language Model InteractionCode1
Evaluating and Mitigating Discrimination in Language Model Decisions—0
Teaching Specific Scientific Knowledge into Large Language Models through Additional TrainingCode0
PneumoLLM: Harnessing the Power of Large Language Model for Pneumoconiosis DiagnosisCode1
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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