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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 34513500 of 17610 papers

TitleStatusHype
Dialogue Action Tokens: Steering Language Models in Goal-Directed Dialogue with a Multi-Turn PlannerCode1
InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction OperatorsCode1
A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human LevelCode1
LLaST: Improved End-to-end Speech Translation System Leveraged by Large Language ModelsCode1
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text GenerationCode1
CTRL: A Conditional Transformer Language Model for Controllable GenerationCode1
INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval ModelsCode1
Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility PredictionCode1
CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language TechnologiesCode1
Sentence Bottleneck Autoencoders from Transformer Language ModelsCode1
CTRAN: CNN-Transformer-based Network for Natural Language UnderstandingCode1
Context-aware Decoding Reduces Hallucination in Query-focused SummarizationCode1
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language ModelCode1
SentiX: A Sentiment-Aware Pre-Trained Model for Cross-Domain Sentiment AnalysisCode1
BootAug: Boosting Text Augmentation via Hybrid Instance Filtering FrameworkCode1
Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language ModelsCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
LLatrieval: LLM-Verified Retrieval for Verifiable GenerationCode1
Context-aware Stand-alone Neural Spelling CorrectionCode1
Integrating Pre-Trained Language Model with Physical Layer CommunicationsCode1
Localized Vision-Language Matching for Open-vocabulary Object DetectionCode1
Intent Representation Learning with Large Language Model for RecommendationCode1
InterControl: Zero-shot Human Interaction Generation by Controlling Every JointCode1
Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action DetectionCode1
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
Cross-Thought for Sentence Encoder Pre-trainingCode1
Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-trainingCode1
SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt TypesCode1
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy RewardCode1
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature InterpretationCode1
LLaMo: Large Language Model-based Molecular Graph AssistantCode1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation ApproachCode1
Shortformer: Better Language Modeling using Shorter InputsCode1
LlamaPartialSpoof: An LLM-Driven Fake Speech Dataset Simulating Disinformation GenerationCode1
LlamaCare: A Large Medical Language Model for Enhancing Healthcare Knowledge SharingCode1
Lite Transformer with Long-Short Range AttentionCode1
Cross-lingual Visual Pre-training for Multimodal Machine TranslationCode1
LI-TTA: Language Informed Test-Time Adaptation for Automatic Speech RecognitionCode1
Inverse Kinematics for Neuro-Robotic Grasping with Humanoid Embodied AgentsCode1
LITE: Modeling Environmental Ecosystems with Multimodal Large Language ModelsCode1
LiteGPT: Large Vision-Language Model for Joint Chest X-ray Localization and Classification TaskCode1
LiveMind: Low-latency Large Language Models with Simultaneous InferenceCode1
SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal ConversationsCode1
Listen, Attend and SpellCode1
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language ModelingCode1
LitCab: Lightweight Language Model Calibration over Short- and Long-form ResponsesCode1
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM UnlearningCode1
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model BiasCode1
A Neural Algorithm of Artistic StyleCode1
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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