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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 30013050 of 17610 papers

TitleStatusHype
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language ModelingCode1
Large Language Model (LLM) as a System of Multiple Expert Agents: An Approach to solve the Abstraction and Reasoning Corpus (ARC) ChallengeCode1
Fine-Tuning InstructPix2Pix for Advanced Image ColorizationCode1
Fine-Tuning Language Models via Epistemic Neural NetworksCode1
CLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-TuningCode1
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context LearningCode1
Large Language Model Can Interpret Latent Space of Sequential RecommenderCode1
Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language ModelsCode1
Cross-Align: Modeling Deep Cross-lingual Interactions for Word AlignmentCode1
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model BiasCode1
ClimateBert: A Pretrained Language Model for Climate-Related TextCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
Queue management for slo-oriented large language model servingCode1
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-CommerceCode1
CDLM: Cross-Document Language ModelingCode1
CriticEval: Evaluating Large Language Model as CriticCode1
Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge EncodingCode1
FinVis-GPT: A Multimodal Large Language Model for Financial Chart AnalysisCode1
FIRE: Fact-checking with Iterative Retrieval and VerificationCode1
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient ReasoningCode1
ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical NotesCode1
Flacuna: Unleashing the Problem Solving Power of Vicuna using FLAN Fine-TuningCode1
Bioformer: an efficient transformer language model for biomedical text miningCode1
Working Memory Capacity of ChatGPT: An Empirical StudyCode1
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic ForgettingCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User SimulatorCode1
Reinforcement Learning Friendly Vision-Language Model for MinecraftCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
BioBERT: a pre-trained biomedical language representation model for biomedical text miningCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
BioBART: Pretraining and Evaluation of A Biomedical Generative Language ModelCode1
Six Dragons Fly Again: Reviving 15th-Century Korean Court Music with Transformers and Novel EncodingCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasCode1
Large Language Model-based Human-Agent Collaboration for Complex Task SolvingCode1
Large Language Model Distilling Medication Recommendation ModelCode1
Large Language Models are not Fair EvaluatorsCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
CrAM: A Compression-Aware MinimizerCode1
Language Model Uncertainty Quantification with Attention ChainCode1
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual ModelsCode1
A Closer Look at the Explainability of Contrastive Language-Image Pre-trainingCode1
FocusLLM: Precise Understanding of Long Context by Dynamic CondensingCode1
Generative Action Description Prompts for Skeleton-based Action RecognitionCode1
FonBund: A Library for Combining Cross-lingual Phonological Segment DataCode1
CLIP-VIS: Adapting CLIP for Open-Vocabulary Video Instance SegmentationCode1
Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language ModelCode1
Show:102550
← PrevPage 61 of 353Next →

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