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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 73517400 of 17610 papers

TitleStatusHype
Anatomy of Neural Language ModelsCode0
Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet0
FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs0
FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference0
The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model PerformanceCode0
A Content-Based Novelty Measure for Scholarly Publications: A Proof of ConceptCode0
Mixtral of ExpertsCode4
DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving0
An Exploratory Study on Automatic Identification of Assumptions in the Development of Deep Learning FrameworksCode0
Maintaining Journalistic Integrity in the Digital Age: A Comprehensive NLP Framework for Evaluating Online News Content0
SeTformer is What You Need for Vision and Language0
CharPoet: A Chinese Classical Poetry Generation System Based on Token-free LLM0
LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward0
Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and ProspectsCode5
Escalation Risks from Language Models in Military and Diplomatic Decision-MakingCode1
Long Context Compression with Activation Beacon0
Enhancing Essay Scoring with Adversarial Weights Perturbation and Metric-specific AttentionPooling0
PIXAR: Auto-Regressive Language Modeling in Pixel Space0
VLLaVO: Mitigating Visual Gap through LLMsCode1
Part-of-Speech Tagger for Bodo Language using Deep Learning approach0
Enhancing Context Through Contrast0
Malla: Demystifying Real-world Large Language Model Integrated Malicious ServicesCode2
Can Large Language Models Understand Molecules?Code1
On the Stability of a non-hyperbolic nonlinear map with non-bounded set of non-isolated fixed points with applications to Machine LearningCode0
Introducing Bode: A Fine-Tuned Large Language Model for Portuguese Prompt-Based Task0
Object-Centric Instruction Augmentation for Robotic Manipulation0
VoroNav: Voronoi-based Zero-shot Object Navigation with Large Language Model0
DocGraphLM: Documental Graph Language Model for Information Extraction0
XUAT-Copilot: Multi-Agent Collaborative System for Automated User Acceptance Testing with Large Language Model0
Thousands of AI Authors on the Future of AI0
ChangeCLIP: Remote sensing change detection with multimodal vision-language representation learningCode2
AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identificationCode0
PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold'em via Large Language Model0
Memory, Consciousness and Large Language Model0
Demonstration of an Adversarial Attack Against a Multimodal Vision Language Model for Pathology ImagingCode0
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment0
Multi-modal vision-language model for generalizable annotation-free pathology localization and clinical diagnosisCode1
LLaVA-Phi: Efficient Multi-Modal Assistant with Small Language ModelCode3
ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction TuningCode2
Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives0
TinyLlama: An Open-Source Small Language ModelCode11
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language ModelCode3
Beyond Extraction: Contextualising Tabular Data for Efficient Summarisation by Language Models0
Understanding LLMs: A Comprehensive Overview from Training to Inference0
Large Language Model Capabilities in Perioperative Risk Prediction and PrognosticationCode0
Cross-target Stance Detection by Exploiting Target Analytical Perspectives0
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling0
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and ToxicityCode2
PLLaMa: An Open-source Large Language Model for Plant ScienceCode1
Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition0
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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