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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 66016650 of 17610 papers

TitleStatusHype
SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language ModelCode1
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic DimensionCode1
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling0
Diffusion Language Models Are Versatile Protein LearnersCode3
A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems0
Grounding Language Models for Visual Entity RecognitionCode1
Learning to Generate Instruction Tuning Datasets for Zero-Shot Task AdaptationCode4
Random Silicon Sampling: Simulating Human Sub-Population Opinion Using a Large Language Model Based on Group-Level Demographic Information0
Datasets for Large Language Models: A Comprehensive SurveyCode5
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented GenerationCode2
CogBench: a large language model walks into a psychology labCode1
Vision Language Model-based Caption Evaluation Method Leveraging Visual Context Extraction0
Is Crowdsourcing Breaking Your Bank? Cost-Effective Fine-Tuning of Pre-trained Language Models with Proximal Policy Optimization0
XMoE: Sparse Models with Fine-grained and Adaptive Expert SelectionCode1
Stable LM 2 1.6B Technical ReportCode0
A Language Model based Framework for New Concept Placement in OntologiesCode1
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A SurveyCode2
Acquiring Linguistic Knowledge from Multimodal Input0
BASES: Large-scale Web Search User Simulation with Large Language Model based Agents0
Automated Statistical Model Discovery with Language Models0
Prediction-Powered Ranking of Large Language ModelsCode0
MATHSENSEI: A Tool-Augmented Large Language Model for Mathematical ReasoningCode0
Tower: An Open Multilingual Large Language Model for Translation-Related TasksCode4
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model RepresentationsCode2
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
Towards Optimal Learning of Language Models0
NextLevelBERT: Masked Language Modeling with Higher-Level Representations for Long DocumentsCode1
Retrieval is Accurate GenerationCode2
OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web0
SongComposer: A Large Language Model for Lyric and Melody Generation in Song CompositionCode3
Large Language Model for Participatory Urban Planning0
ShapeLLM: Universal 3D Object Understanding for Embodied InteractionCode3
CARZero: Cross-Attention Alignment for Radiology Zero-Shot ClassificationCode2
VCD: Knowledge Base Guided Visual Commonsense Discovery in Images0
A Neural Rewriting System to Solve Algorithmic Problems0
Read and Think: An Efficient Step-wise Multimodal Language Model for Document Understanding and Reasoning0
Retrieval Augmented Generation Systems: Automatic Dataset Creation, Evaluation and Boolean Agent SetupCode0
LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic SurgeryCode0
OncoGPT: A Medical Conversational Model Tailored with Oncology Domain Expertise on a Large Language Model Meta-AI (LLaMA)0
Long-Context Language Modeling with Parallel Context EncodingCode2
ESG Sentiment Analysis: comparing human and language model performance including GPT0
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding0
Pandora's White-Box: Precise Training Data Detection and Extraction in Large Language ModelsCode2
CodeS: Towards Building Open-source Language Models for Text-to-SQLCode2
GROUNDHOG: Grounding Large Language Models to Holistic Segmentation0
Cross-Modal Projection in Multimodal LLMs Doesn't Really Project Visual Attributes to Textual SpaceCode1
A Comprehensive Evaluation of Quantization Strategies for Large Language ModelsCode0
Nemotron-4 15B Technical Report0
RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation GenerationCode4
LLM Inference Unveiled: Survey and Roofline Model InsightsCode4
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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