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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 61516200 of 17610 papers

TitleStatusHype
Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework0
The New Agronomists: Language Models are Experts in Crop ManagementCode1
Make Large Language Model a Better Ranker0
HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding0
Localizing Paragraph Memorization in Language ModelsCode1
Jamba: A Hybrid Transformer-Mamba Language ModelCode0
ChatTracer: Large Language Model Powered Real-time Bluetooth Device Tracking System0
Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical DataCode0
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage ScenariosCode3
Evolving Assembly Code in an Adversarial EnvironmentCode0
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and AnalysisCode2
BP4ER: Bootstrap Prompting for Explicit Reasoning in Medical Dialogue Generation0
Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous DrivingCode2
Developing Healthcare Language Model Embedding Spaces0
IVLMap: Instance-Aware Visual Language Grounding for Consumer Robot Navigation0
Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation0
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question AnsweringCode1
InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction0
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language ModelsCode3
STaR-GATE: Teaching Language Models to Ask Clarifying QuestionsCode1
What are human values, and how do we align AI to them?0
Envisioning MedCLIP: A Deep Dive into Explainability for Medical Vision-Language Models0
Reshaping Free-Text Radiology Notes Into Structured Reports With Generative TransformersCode0
Homogeneous Tokenizer Matters: Homogeneous Visual Tokenizer for Remote Sensing Image UnderstandingCode1
Common Sense Enhanced Knowledge-based Recommendation with Large Language ModelCode1
CheckEval: Robust Evaluation Framework using Large Language Model via Checklist0
LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models0
Leveraging Large Language Models for Relevance Judgments in Legal Case Retrieval0
Content-Based Collaborative Generation for Recommender SystemsCode1
Sequential Recommendation with Latent Relations based on Large Language ModelCode1
The Invalsi Benchmarks: measuring Linguistic and Mathematical understanding of Large Language Models in Italian0
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory PredictionCode2
Mechanistic Understanding and Mitigation of Language Model Non-Factual HallucinationsCode0
Projective Methods for Mitigating Gender Bias in Pre-trained Language ModelsCode0
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical TextCode4
Towards a World-English Language Model for On-Device Virtual Assistants0
mALBERT: Is a Compact Multilingual BERT Model Still Worth It?0
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLMCode2
Is Modularity Transferable? A Case Study through the Lens of Knowledge DistillationCode0
Fingerprinting web servers through Transformer-encoded HTTP response headersCode0
Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NERCode0
Juru: Legal Brazilian Large Language Model from Reputable Sources0
Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models using Minimal Pairs0
DANCER: Entity Description Augmented Named Entity Corrector for Automatic Speech Recognition0
JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue DatasetCode1
Improving Text-to-Image Consistency via Automatic Prompt Optimization0
ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching0
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-TuningCode9
MIND Your Language: A Multilingual Dataset for Cross-lingual News RecommendationCode2
Towards a Zero-Data, Controllable, Adaptive Dialog System0
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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