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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 63516400 of 17610 papers

TitleStatusHype
Tokensome: Towards a Genetic Vision-Language GPT for Explainable and Cognitive Karyotyping0
Large language model-powered chatbots for internationalizing student support in higher education0
Integrating Wearable Sensor Data and Self-reported Diaries for Personalized Affect Forecasting0
Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm Maximization0
Initial Decoding with Minimally Augmented Language Model for Improved Lattice Rescoring in Low Resource ASR0
Energy-Based Models with Applications to Speech and Language Processing0
Detecting Bias in Large Language Models: Fine-tuned KcBERT0
SelfIE: Self-Interpretation of Large Language Model EmbeddingsCode2
Exploring Chinese Humor Generation: A Study on Two-Part Allegorical Sayings0
GAgent: An Adaptive Rigid-Soft Gripping Agent with Vision Language Models for Complex Lighting Environments0
Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment0
On Recovering Higher-order Interactions from Protein Language ModelsCode0
ChatPattern: Layout Pattern Customization via Natural Language0
Ignore Me But Don't Replace Me: Utilizing Non-Linguistic Elements for Pretraining on the Cybersecurity Domain0
Leveraging vision-language models for fair facial attribute classification0
DiPaCo: Distributed Path Composition0
Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection0
TextBlockV2: Towards Precise-Detection-Free Scene Text Spotting with Pre-trained Language Model0
Generative Region-Language Pretraining for Open-Ended Object DetectionCode2
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk PredictionCode1
MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling0
Using an LLM to Turn Sign Spottings into Spoken Language Sentences0
Improving Medical Multi-modal Contrastive Learning with Expert AnnotationsCode0
RAFT: Adapting Language Model to Domain Specific RAGCode0
CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language ModelCode1
Enhancing Human-Centered Dynamic Scene Understanding via Multiple LLMs Collaborated Reasoning0
VideoAgent: Long-form Video Understanding with Large Language Model as AgentCode2
EfficientVMamba: Atrous Selective Scan for Light Weight Visual MambaCode3
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement LearningCode0
What Was Your Prompt? A Remote Keylogging Attack on AI AssistantsCode2
Fisher Mask Nodes for Language Model MergingCode0
Right Place, Right Time! Dynamizing Topological Graphs for Embodied Navigation0
B-AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Black-box Adversarial Visual-InstructionsCode0
Semiparametric Token-Sequence Co-SupervisionCode0
Logits of API-Protected LLMs Leak Proprietary Information0
ProSwitch: Knowledge-Guided Instruction Tuning to Switch Between Professional and Non-Professional Responses0
Quiet-STaR: Language Models Can Teach Themselves to Think Before SpeakingCode4
LAMP: A Language Model on the MapCode0
Logical Discrete Graphical Models Must Supplement Large Language Models for Information Synthesis0
AI on AI: Exploring the Utility of GPT as an Expert Annotator of AI Publications0
GiT: Towards Generalist Vision Transformer through Universal Language InterfaceCode3
VisionGPT: Vision-Language Understanding Agent Using Generalized Multimodal Framework0
3D-VLA: A 3D Vision-Language-Action Generative World Model0
Anomaly Detection by Adapting a pre-trained Vision Language Model0
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language ModelsCode1
Do Large Language Models Solve ARC Visual Analogies Like People Do?Code0
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents0
Bifurcated Attention: Accelerating Massively Parallel Decoding with Shared Prefixes in LLMs0
CoIN: A Benchmark of Continual Instruction tuNing for Multimodel Large Language ModelCode2
Masked Generative Story Transformer with Character Guidance and Caption AugmentationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified