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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 7401–7450 of 17610 papers

TitleStatusHype
Speech and Language Resources for LVCSR of Russian—0
Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction—0
SpeechBERT: An Audio-and-text Jointly Learned Language Model for End-to-end Spoken Question Answering—0
SpeechComposer: Unifying Multiple Speech Tasks with Prompt Composition—0
Speech Disfluencies occur at Higher Perplexities—0
Speech-language Pre-training for End-to-end Spoken Language Understanding—0
SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data—0
SpeechPrompt: Prompting Speech Language Models for Speech Processing Tasks—0
SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks—0
Speech Recognition by Simply Fine-tuning BERT—0
Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning—0
Speech Retrieval-Augmented Generation without Automatic Speech Recognition—0
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network—0
Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning—0
Speech Token Prediction via Compressed-to-fine Language Modeling for Speech Generation—0
Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer—0
Speech-to-Text Adapter and Speech-to-Entity Retriever Augmented LLMs for Speech Understanding—0
Speech Transcription Challenges for Resource Constrained Indigenous Language Cree—0
Speech Translation with Large Language Models: An Industrial Practice—0
SpeechVerse: A Large-scale Generalizable Audio Language Model—0
SpeechX: Neural Codec Language Model as a Versatile Speech Transformer—0
SpellBERT: A Lightweight Pretrained Model for Chinese Spelling Check—0
Spelling-Aware Construction of Macaronic Texts for Teaching Foreign-Language Vocabulary—0
Spelling convention sensitivity in neural language models—0
Spelling Correction as a Foreign Language—0
Spelling Correction for Morphologically Rich Language: a Case Study of Russian—0
SPICED: Syntactical Bug and Trojan Pattern Identification in A/MS Circuits using LLM-Enhanced Detection—0
Spike No More: Stabilizing the Pre-training of Large Language Models—0
Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering—0
Spiral Language Modeling—0
SPL: A Socratic Playground for Learning Powered by Large Language Model—0
Split and Merge: Aligning Position Biases in LLM-based Evaluators—0
Split-and-Rephrase in a Cross-Lingual Manner: A Complete Pipeline—0
SplitReason: Learning To Offload Reasoning—0
Splitting compounds with ngrams—0
SPM: Structured Pretraining and Matching Architectures for Relevance Modeling in Meituan Search—0
SPOCK at FinCausal 2022: Causal Information Extraction Using Span-Based and Sequence Tagging Models—0
Spoken Grammar Assessment Using LLM—0
Spoken Language Identification with Phonotactics Methods on Minangkabau, Sundanese, and Javanese Languages—0
Spoken Language Translation for Polish—0
Spontaneous Emergence of Agent Individuality through Social Interactions in LLM-Based Communities—0
Spontaneous Emerging Preference in Two-tower Language Model—0
Spontaneous Reward Hacking in Iterative Self-Refinement—0
Spontaneous Style Text-to-Speech Synthesis with Controllable Spontaneous Behaviors Based on Language Models—0
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer—0
Spotlight: Mobile UI Understanding using Vision-Language Models with a Focus—0
SPRING Lab IITM's submission to Low Resource Indic Language Translation Shared Task—0
SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning—0
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)—0
Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model—0
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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