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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9601–9650 of 17610 papers

TitleStatusHype
Long-Short Range Context Neural Networks for Language Modeling—0
LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models—0
Long-span language modeling for speech recognition—0
LongSSM: On the Length Extension of State-space Models in Language Modelling—0
LongSumm 2021: Session based automatic summarization model for scientific document—0
Long-Tail Crisis in Nearest Neighbor Language Models—0
Long-Tailed Question Answering in an Open World—0
Long-Tail Predictions with Continuous-Output Language Models—0
Long-Term Ad Memorability: Understanding & Generating Memorable Ads—0
LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory—0
Look Before You Leap: Using Serialized State Machine for Language Conditioned Robotic Manipulation—0
Looking beyond the next token—0
Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling—0
Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling—0
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing—0
Lookup-Table Recurrent Language Models for Long Tail Speech Recognition—0
Loop Neural Networks for Parameter Sharing—0
Loose lips sink ships: Mitigating Length Bias in Reinforcement Learning from Human Feedback—0
LoPT: Low-Rank Prompt Tuning for Parameter Efficient Language Models—0
LoRA ensembles for large language model fine-tuning—0
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades—0
LoRE: Logit-Ranked Retriever Ensemble for Enhancing Open-Domain Question Answering—0
LoRE-Merging: Exploring Low-Rank Estimation For Large Language Model Merging—0
LoRS: Efficient Low-Rank Adaptation for Sparse Large Language Model—0
Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training—0
Loss Functions and Operators Generated by f-Divergences—0
Lossless Compression of Large Language Model-Generated Text via Next-Token Prediction—0
Lossless Data Compression with Transformer—0
Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues—0
Lost in Translation: When GPT-4V(ision) Can't See Eye to Eye with Text. A Vision-Language-Consistency Analysis of VLLMs and Beyond—0
Low-dimensional Query Projection based on Divergence Minimization Feedback Model for Ad-hoc Retrieval—0
Low Frame-rate Speech Codec: a Codec Designed for Fast High-quality Speech LLM Training and Inference—0
Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training—0
Low-Latency Incremental Text-to-Speech Synthesis with Distilled Context Prediction Network—0
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition—0
Low-Rank Prune-And-Factorize for Language Model Compression—0
Low-Resource ASR with an Augmented Language Model—0
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System—0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey—0
Low-Resource Machine Translation Training Curriculum Fit for Low-Resource Languages—0
Low-Resource Machine Translation Using Cross-Lingual Language Model Pretraining—0
Low-resource OCR error detection and correction in French Clinical Texts—0
Low-resource speech recognition and dialect identification of Irish in a multi-task framework—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Low-Resource Text Classification via Cross-lingual Language Model Fine-tuning—0
Low-Resource Translation as Language Modeling—0
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models—0
LProtector: An LLM-driven Vulnerability Detection System—0
LPZero: Language Model Zero-cost Proxy Search from Zero—0
Show:102550
← PrevPage 193 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