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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1495115000 of 17610 papers

TitleStatusHype
Rank-K: Test-Time Reasoning for Listwise RerankingCode0
Thank You, Stingray: Multilingual Large Language Models Can Not (Yet) Disambiguate Cross-Lingual Word SenseCode0
Thanos: A Block-wise Pruning Algorithm for Efficient Large Language Model CompressionCode0
Thanos: Enhancing Conversational Agents with Skill-of-Mind-Infused Large Language ModelCode0
That Looks Hard: Characterizing Linguistic Complexity in Humans and Language ModelsCode0
Ranking Unraveled: Recipes for LLM Rankings in Head-to-Head AI CombatCode0
Ranking Manipulation for Conversational Search EnginesCode0
Retro-li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift GeneralizationCode0
Randomized Geometric Algebra Methods for Convex Neural NetworksCode0
Returning to the Start: Generating Narratives with Related EndpointsCode0
RALLRec+: Retrieval Augmented Large Language Model Recommendation with ReasoningCode0
RAFT: Adapting Language Model to Domain Specific RAGCode0
Learning to Verify Summary Facts with Fine-Grained LLM FeedbackCode0
RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health InterviewsCode0
Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-PlayingCode0
Revealing the structure of language model capabilitiesCode0
Language Model Adaptation to Specialized Domains through Selective Masking based on Genre and Topical CharacteristicsCode0
Revealing Vision-Language Integration in the Brain with Multimodal NetworksCode0
REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge MemoryCode0
Spoken Language Modeling with Duration-Penalized Self-Supervised UnitsCode0
Reverse-Engineering the ReaderCode0
Localization of Fake News Detection via Multitask Transfer LearningCode0
Spoken ObjectNet: A Bias-Controlled Spoken Caption DatasetCode0
Review Conversational Reading ComprehensionCode0
Local and Global Decoding in Text GenerationCode0
Knowledge-Augmented Language Model and its Application to Unsupervised Named-Entity RecognitionCode0
Topic Classification of Case Law Using a Large Language Model and a New Taxonomy for UK Law: AI Insights into Summary JudgmentCode0
Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPTCode0
Knowing Where and What: Unified Word Block Pretraining for Document UnderstandingCode0
The AI-KU System at the SPMRL 2013 Shared Task : Unsupervised Features for Dependency ParsingCode0
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLMCode0
Multimodal Latent Language Modeling with Next-Token DiffusionCode0
Language-Enhanced Representation Learning for Single-Cell TranscriptomicsCode0
Question-Instructed Visual Descriptions for Zero-Shot Video Question AnsweringCode0
Question answering system of bridge design specification based on large language modelCode0
SPRIG: Improving Large Language Model Performance by System Prompt OptimizationCode0
Revisiting Counterfactual Problems in Referring Expression ComprehensionCode0
Multimodal Hypothetical Summary for Retrieval-based Multi-image Question AnsweringCode0
LM-CORE: Language Models with Contextually Relevant External KnowledgeCode0
WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical CaseCode0
Revisiting Few-Shot Object Detection with Vision-Language ModelsCode0
QueerBench: Quantifying Discrimination in Language Models Toward Queer IdentitiesCode0
QUDEVAL: The Evaluation of Questions Under Discussion Discourse ParsingCode0
Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model AttributionCode0
Multimodal Embeddings from Language ModelsCode0
Spuriousness-Aware Meta-Learning for Learning Robust ClassifiersCode0
Quasi-Recurrent Neural NetworksCode0
Quantized Prompt for Efficient Generalization of Vision-Language ModelsCode0
Multilingual unsupervised sequence segmentation transfers to extremely low-resource languagesCode0
Quantifying Gender Bias Towards Politicians in Cross-Lingual Language ModelsCode0
Show:102550
← PrevPage 300 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