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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 40514100 of 17610 papers

TitleStatusHype
Abstract Operations Research Modeling Using Natural Language Inputs0
Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference0
Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach0
ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry AreaCode2
Development of a Large Language Model-based Multi-Agent Clinical Decision Support System for Korean Triage and Acuity Scale (KTAS)-Based Triage and Treatment Planning in Emergency Departments0
MGH Radiology Llama: A Llama 3 70B Model for Radiology0
Style-Talker: Finetuning Audio Language Model and Style-Based Text-to-Speech Model for Fast Spoken Dialogue Generation0
Vision Language Model for Interpretable and Fine-grained Detection of Safety Compliance in Diverse Workplaces0
A semantic embedding space based on large language models for modelling human beliefsCode1
Unlocking Efficiency: Adaptive Masking for Gene Transformer ModelsCode0
Response Wide Shut: Surprising Observations in Basic Vision Language Model Capabilities0
CROME: Cross-Modal Adapters for Efficient Multimodal LLM0
DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs0
SceneGPT: A Language Model for 3D Scene Understanding0
The advantages of context specific language models: the case of the Erasmian Language ModelCode1
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model0
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents0
Causal Agent based on Large Language ModelCode2
Casper: Prompt Sanitization for Protecting User Privacy in Web-Based Large Language Models0
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out StrategiesCode1
Evaluating Cultural Adaptability of a Large Language Model via Simulation of Synthetic PersonasCode0
IFShip: Interpretable Fine-grained Ship Classification with Domain Knowledge-Enhanced Vision-Language ModelsCode0
AGE: Amharic, Ge’ez and English Parallel Dataset0
Prompto: An open source library for asynchronous querying of LLM endpointsCode1
XCompress: LLM assisted Python-based text compression toolkitCode0
FuxiTranyu: A Multilingual Large Language Model Trained with Balanced DataCode1
Creating Arabic LLM Prompts at Scale0
Towards Autonomous Agents: Adaptive-planning, Reasoning, and Acting in Language Models0
LUT Tensor Core: A Software-Hardware Co-Design for LUT-Based Low-Bit LLM Inference0
LipidBERT: A Lipid Language Model Pre-trained on METiS de novo Lipid Library0
Global-to-Local Support Spectrums for Language Model Explainability0
Space-LLaVA: a Vision-Language Model Adapted to Extraterrestrial Applications0
The AI Scientist: Towards Fully Automated Open-Ended Scientific DiscoveryCode11
On Effects of Steering Latent Representation for Large Language Model UnlearningCode0
Building Decision Making Models Through Language Model Regime0
LI-TTA: Language Informed Test-Time Adaptation for Automatic Speech RecognitionCode1
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERTCode1
Path-LLM: A Shortest-Path-based LLM Learning for Unified Graph Representation0
Large Language Model-based Role-Playing for Personalized Medical Jargon Extraction0
Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text0
Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion0
ViC: Virtual Compiler Is All You Need For Assembly Code SearchCode1
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at ScaleCode3
LLaMA based Punctuation Restoration With Forward Pass Only Decoding0
Node Level Graph Autoencoder: Unified Pretraining for Textual Graph Learning0
Report on the 1st Workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) at SIGIR 20240
mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language ModelsCode7
Unleashing Artificial Cognition: Integrating Multiple AI SystemsCode1
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model0
Improving Mortality Prediction After Radiotherapy with Large Language Model Structuring of Large-Scale Unstructured Electronic Health Records0
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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