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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 5051–5100 of 17610 papers

TitleStatusHype
Contrastive learning of T cell receptor representationsCode0
Towards a Personal Health Large Language Model—0
NarrativeBridge: Enhancing Video Captioning with Causal-Temporal Narrative—0
Parallelizing Linear Transformers with the Delta Rule over Sequence Length—0
A Large Language Model Pipeline for Breast Cancer Oncology—0
Solution for SMART-101 Challenge of CVPR Multi-modal Algorithmic Reasoning Task 2024—0
AID: Adapting Image2Video Diffusion Models for Instruction-guided Video Prediction—0
Tx-LLM: A Large Language Model for Therapeutics—0
Transforming Wearable Data into Health Insights using Large Language Model Agents—0
PowerInfer-2: Fast Large Language Model Inference on a SmartphoneCode9
VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded TextCode1
Diffusion-RPO: Aligning Diffusion Models through Relative Preference OptimizationCode1
Soundscape Captioning using Sound Affective Quality Network and Large Language ModelCode1
Text-aware and Context-aware Expressive Audiobook Speech Synthesis—0
LLM Questionnaire Completion for Automatic Psychiatric Assessment—0
MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations—0
GrowOVER: How Can LLMs Adapt to Growing Real-World Knowledge?Code0
Seventeenth-Century Spanish American Notary Records for Fine-Tuning Spanish Large Language ModelsCode0
A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback LearningCode3
A Superalignment Framework in Autonomous Driving with Large Language Models—0
A Knowledge-Component-Based Methodology for Evaluating AI Assistants—0
Digital Business Model Analysis Using a Large Language Model—0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender SystemCode0
Critical Phase Transition in Large Language Models—0
Exploring the Benefits of Tokenization of Discrete Acoustic Units—0
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey—0
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification—0
Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language ModelsCode0
Fighting Against the Repetitive Training and Sample Dependency Problem in Few-shot Named Entity Recognition—0
A Fine-tuning Dataset and Benchmark for Large Language Models for Protein UnderstandingCode1
ChatPCG: Large Language Model-Driven Reward Design for Procedural Content Generation—0
Boosting Diffusion Model for Spectrogram Up-sampling in Text-to-speech: An Empirical Study—0
Accelerating evolutionary exploration through language model-based transfer learning—0
MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal LearningCode1
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-AnsweringCode1
CRAG -- Comprehensive RAG BenchmarkCode3
Mixture-of-Agents Enhances Large Language Model CapabilitiesCode7
Large Language Model-guided Document Selection—0
A Language Model-Guided Framework for Mining Time Series with Distributional Shifts—0
Do Language Models Exhibit Human-like Structural Priming Effects?Code0
LLM-POET: Evolving Complex Environments using Large Language Models—0
Uncertainty Aware Learning for Language Model Alignment—0
Quantifying Geospatial in the Common Crawl Corpus—0
LocLLM: Exploiting Generalizable Human Keypoint Localization via Large Language ModelCode2
MATTER: Memory-Augmented Transformer Using Heterogeneous Knowledge Sources—0
Revisiting Catastrophic Forgetting in Large Language Model TuningCode1
CityCraft: A Real Crafter for 3D City Generation—0
Large Generative Graph Models—0
LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses—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