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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 10051–10100 of 17610 papers

TitleStatusHype
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models—0
Optimizing Singular Spectrum for Large Language Model Compression—0
Optimizing the Design of an Artificial Pancreas to Improve Diabetes Management—0
Optimizing Token Usage on Large Language Model Conversations Using the Design Structure Matrix—0
Optimizing Vision-Language Interactions Through Decoder-Only Models—0
Oracle-Checker Scheme for Evaluating a Generative Large Language Model—0
OrcaLoca: An LLM Agent Framework for Software Issue Localization—0
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling—0
Orchestrate Multimodal Data with Batch Post-Balancing to Accelerate Multimodal Large Language Model Training—0
Order-agnostic Identifier for Large Language Model-based Generative Recommendation—0
Order Independence With Finetuning—0
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning—0
Ornithologist: Towards Trustworthy "Reasoning" about Central Bank Communications—0
ORQA: A Benchmark and Foundation Model for Holistic Operating Room Modeling—0
OrthoDoc: Multimodal Large Language Model for Assisting Diagnosis in Computed Tomography—0
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads—0
OSIC: A New One-Stage Image Captioner Coined—0
OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst—0
Outlier dimensions favor frequent tokens in language models—0
Test-Time Fairness and Robustness in Large Language Models—0
Out-of-Distribution Detection Using Peer-Class Generated by Large Language Model—0
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models—0
Out of One, Many: Using Language Models to Simulate Human Samples—0
OVEL: Large Language Model as Memory Manager for Online Video Entity Linking—0
Overcoming Data Scarcity in Generative Language Modelling for Low-Resource Languages: A Systematic Review—0
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts—0
Overcoming linguistic barriers in code assistants: creating a QLoRA adapter to improve support for Russian-language code writing instructions—0
Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling—0
Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling—0
"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalism—0
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning—0
π_0: A Vision-Language-Action Flow Model for General Robot Control—0
P^3LM: Probabilistically Permuted Prophet Language Modeling for Generative Pre-Training—0
PACE: Improving Prompt with Actor-Critic Editing for Large Language Model—0
PADriver: Towards Personalized Autonomous Driving—0
PaECTER: Patent-level Representation Learning using Citation-informed Transformers—0
Pagination: It's what you say, not how long it takes to say it—0
Painless Semi-Supervised Morphological Segmentation using Conditional Random Fields—0
PairConnect: A Compute-Efficient MLP Alternative to Attention—0
Pair Programming with Large Language Models for Sampling and Estimation of Copulas—0
PaliGemma: A versatile 3B VLM for transfer—0
PaLM 2 Technical Report—0
PaLM2-VAdapter: Progressively Aligned Language Model Makes a Strong Vision-language Adapter—0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation—0
Paloma: A Benchmark for Evaluating Language Model Fit—0
Palomino-Ochoa at SemEval-2020 Task 9: Robust System based on Transformer for Code-Mixed Sentiment Classification—0
Panacea: Pareto Alignment via Preference Adaptation for LLMs—0
Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge—0
PANDORA: Diffusion Policy Learning for Dexterous Robotic Piano Playing—0
PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation—0
Show:102550
← PrevPage 202 of 353Next →
All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified