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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 2901–2950 of 17610 papers

TitleStatusHype
From melodic note sequences to pitches using word2vec—0
An Actor-Critic Approach to Boosting Text-to-SQL Large Language Model—0
LLMCBench: Benchmarking Large Language Model Compression for Efficient DeploymentCode1
PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation—0
Can Machines Think Like Humans? A Behavioral Evaluation of LLM-Agents in Dictator Games—0
Large Language Model Benchmarks in Medical Tasks—0
Thank You, Stingray: Multilingual Large Language Models Can Not (Yet) Disambiguate Cross-Lingual Word SenseCode0
Energy-Based Diffusion Language Models for Text Generation—0
Large Language Model-Guided Prediction Toward Quantum Materials SynthesisCode0
Visualizing attention zones in machine reading comprehension models—0
Segmenting Watermarked Texts From Language ModelsCode0
ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents—0
Rephrasing natural text data with different languages and quality levels for Large Language Model pre-training—0
Graph-based Uncertainty Metrics for Long-form Language Model OutputsCode0
Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language ModelCode2
Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback—0
Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce—0
Stealthy Jailbreak Attacks on Large Language Models via Benign Data Mirroring—0
BongLLaMA: LLaMA for Bangla Language—0
Large Language Model-assisted Speech and Pointing Benefits Multiple 3D Object Selection in Virtual Reality—0
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models—0
TrajAgent: An Agent Framework for Unified Trajectory ModellingCode1
R^3AG: First Workshop on Refined and Reliable Retrieval Augmented Generation—0
MedGo: A Chinese Medical Large Language Model—0
Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse AutoencodersCode3
Sequential Large Language Model-Based Hyper-parameter OptimizationCode0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation—0
Chemical Language Model Linker: blending text and molecules with modular adaptersCode0
Centaur: a foundation model of human cognitionCode3
A Multimodal Approach For Endoscopic VCE Image Classification Using BiomedCLIP-PubMedBERTCode0
Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model—0
COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 TrainingCode3
Computational Bottlenecks of Training Small-scale Large Language Models—0
IPPON: Common Sense Guided Informative Path Planning for Object Goal Navigation—0
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic SupervisionCode1
EDGE: Enhanced Grounded GUI Understanding with Enriched Multi-Granularity Synthetic Data—0
GCoder: Improving Large Language Model for Generalized Graph Problem SolvingCode1
AlignCap: Aligning Speech Emotion Captioning to Human Preferences—0
FedBaF: Federated Learning Aggregation Biased by a Foundation Model—0
Taipan: Efficient and Expressive State Space Language Models with Selective Attention—0
Scaling up Masked Diffusion Models on TextCode3
Zero-shot Object Navigation with Vision-Language Models Reasoning—0
A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs—0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
Structure Language Models for Protein Conformation Generation—0
Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms—0
Provably Robust Watermarks for Open-Source Language Models—0
Bielik 7B v0.1: A Polish Language Model -- Development, Insights, and Evaluation—0
Unbounded: A Generative Infinite Game of Character Life Simulation—0
LOGO -- Long cOntext aliGnment via efficient preference OptimizationCode1
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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