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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 18511900 of 17610 papers

TitleStatusHype
How Language Model Hallucinations Can SnowballCode1
KGLM: Integrating Knowledge Graph Structure in Language Models for Link PredictionCode1
KinyaBERT: a Morphology-aware Kinyarwanda Language ModelCode1
Do Large Language Model Benchmarks Test Reliability?Code1
Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue SystemsCode1
Automatic Label Sequence Generation for Prompting Sequence-to-sequence ModelsCode1
Heterogeneous Graph Reasoning for Fact Checking over Texts and TablesCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
A Multi-Modal Context Reasoning Approach for Conditional Inference on Joint Textual and Visual CluesCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
Automatic Model Selection with Large Language Models for ReasoningCode1
ADCNet: a unified framework for predicting the activity of antibody-drug conjugatesCode1
Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot ClassificationCode1
MGeo: Multi-Modal Geographic Pre-Training MethodCode1
A Multimodal In-Context Tuning Approach for E-Commerce Product Description GenerationCode1
DOMINO: A Dual-System for Multi-step Visual Language ReasoningCode1
Cross-Align: Modeling Deep Cross-lingual Interactions for Word AlignmentCode1
Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysisCode1
HetSeq: Distributed GPU Training on Heterogeneous InfrastructureCode1
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataCode1
Enhancing Monocular 3D Scene Completion with Diffusion ModelCode1
Do Unlearning Methods Remove Information from Language Model Weights?Code1
CriticEval: Evaluating Large Language Model as CriticCode1
A Surprisingly Robust Trick for Winograd Schema ChallengeCode1
Downstream Model Design of Pre-trained Language Model for Relation Extraction TaskCode1
Hespi: A pipeline for automatically detecting information from hebarium specimen sheetsCode1
A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement PredictionCode1
Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling InsightsCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World ClaimsCode1
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-trainingCode1
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsCode1
Hessian of Perplexity for Large Language Models by PyTorch autograd (Open Source)Code1
Hexatagging: Projective Dependency Parsing as TaggingCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
DRG-LLaMA : Tuning LLaMA Model to Predict Diagnosis-related Group for Hospitalized PatientsCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code SynthesisCode1
KR-BERT: A Small-Scale Korean-Specific Language ModelCode1
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZCode1
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward HackingCode1
Salmon: A Suite for Acoustic Language Model EvaluationCode1
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-TuningCode1
L2MAC: Large Language Model Automatic Computer for Extensive Code GenerationCode1
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model BiasCode1
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model PredictionsCode1
Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry WritingCode1
A Large Scale Search Dataset for Unbiased Learning to RankCode1
Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code GenerationCode1
CrAM: A Compression-Aware MinimizerCode1
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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