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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 6751–6800 of 17610 papers

TitleStatusHype
Binary Classifier Optimization for Large Language Model Alignment—0
BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning—0
BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition—0
BioAtt: Anatomical Prior Driven Low-Dose CT Denoising—0
BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition—0
Bioinformatics and Biomedical Informatics with ChatGPT: Year One Review—0
BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials—0
Bio-Inspired Mamba: Temporal Locality and Bioplausible Learning in Selective State Space Models—0
Bio-inspired Structure Identification in Language Embeddings—0
BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing—0
Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformers—0
BiomechGPT: Towards a Biomechanically Fluent Multimodal Foundation Model for Clinically Relevant Motion Tasks—0
BioMedBERT: A Pre-trained Biomedical Language Model for QA and IR—0
Biomed-Enriched: A Biomedical Dataset Enriched with LLMs for Pretraining and Extracting Rare and Hidden Content—0
BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine—0
Biomedical Chinese-English CLIR Using an Extended CMeSH Resource to Expand Queries—0
Biomedical Nested NER with Large Language Model and UMLS Heuristics—0
Biomedical Question Answering via Multi-Level Summarization on a Local Knowledge Graph—0
Biomedical relation extraction with pre-trained language representations and minimal task-specific architecture—0
BioMegatron: Larger Biomedical Domain Language Model—0
Birds of a Feather Flock Together: Satirical News Detection via Language Model Differentiation—0
Birzeit Arabic Dialect Identification System for the 2018 VarDial Challenge—0
BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models—0
BitNet b1.58 2B4T Technical Report—0
Bi-VLDoc: Bidirectional Vision-Language Modeling for Visually-Rich Document Understanding—0
Black-Box Detection of Language Model Watermarks—0
FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair—0
Blessing of Class Diversity in Pre-training—0
BLIAM: Literature-based Data Synthesis for Synergistic Drug Combination Prediction—0
Bloated Disclosures: Can ChatGPT Help Investors Process Information?—0
Block-Biased Mamba for Long-Range Sequence Processing—0
Blockchain for Large Language Model Security and Safety: A Holistic Survey—0
Blockchain Large Language Models—0
Block-level Text Spotting with LLMs—0
Block Skim Transformer for Efficient Question Answering—0
Block-Sparse Recurrent Neural Networks—0
Block-State Transformers—0
BloombergGPT: A Large Language Model for Finance—0
Bloom Library: Multimodal Datasets in 300+ Languages for a Variety of Downstream Tasks—0
BLP-2023 Task 2: Sentiment Analysis—0
B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory—0
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL—0
BongLLaMA: LLaMA for Bangla Language—0
BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model—0
BOOST: Harnessing Black-Box Control to Boost Commonsense in LMs' Generation—0
Boosting Code-Switching ASR with Mixture of Experts Enhanced Speech-Conditioned LLM—0
Boosting Diffusion Model for Spectrogram Up-sampling in Text-to-speech: An Empirical Study—0
Boosting Few-Shot Detection with Large Language Models and Layout-to-Image Synthesis—0
Boosting Large Language Model for Speech Synthesis: An Empirical Study—0
Boosting Large Language Models with Continual Learning for Aspect-based Sentiment Analysis—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