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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 79017950 of 17610 papers

TitleStatusHype
Beyond Turing: A Comparative Analysis of Approaches for Detecting Machine-Generated Text0
BEND: Benchmarking DNA Language Models on biologically meaningful tasksCode1
KBioXLM: A Knowledge-anchored Biomedical Multilingual Pretrained Language ModelCode0
Adapt in Contexts: Retrieval-Augmented Domain Adaptation via In-Context Learning0
Fingerspelling PoseNet: Enhancing Fingerspelling Translation with Pose-Based Transformer ModelsCode0
Unifying Corroborative and Contributive Attributions in Large Language Models0
NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation0
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model FinetuningCode1
GPT-4V(ision) for Robotics: Multimodal Task Planning from Human Demonstration0
Taiyi: A Bilingual Fine-Tuned Large Language Model for Diverse Biomedical TasksCode1
Refactoring Programs Using Large Language Models with Few-Shot Examples0
Fine-Tuning Adaptive Stochastic Optimizers: Determining the Optimal Hyperparameter ε via Gradient Magnitude Histogram Analysis0
Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement0
Causal Structure Learning Supervised by Large Language ModelCode1
LION : Empowering Multimodal Large Language Model with Dual-Level Visual KnowledgeCode1
Meta Prompting for AI SystemsCode2
DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding0
Zero-Shot Question Answering over Financial Documents using Large Language Models0
SecureBERT and LLAMA 2 Empowered Control Area Network Intrusion Detection and Classification0
Label-Synchronous Neural Transducer for Adaptable Online E2E Speech Recognition0
Open-Vocabulary Camouflaged Object SegmentationCode2
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems0
Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object DetectionCode0
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language ModelsCode4
Representing visual classification as a linear combination of wordsCode0
A Principled Framework for Knowledge-enhanced Large Language Model0
Flexible Model Interpretability through Natural Language Model Editing0
Causal Graph in Language Model Rediscovers Cortical Hierarchy in Human Narrative Processing0
Energy and Carbon Considerations of Fine-Tuning BERT0
DynaPipe: Optimizing Multi-task Training through Dynamic PipelinesCode1
LE-SSL-MOS: Self-Supervised Learning MOS Prediction with Listener Enhancement0
On Functional Activations in Deep Neural Networks0
Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads0
PEFT-MedAware: Large Language Model for Medical Awareness0
Testing Language Model Agents Safely in the Wild0
Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language CorrectionsCode1
Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis0
Can Language Model Moderators Improve the Health of Online Discourse?0
Strings from the Library of Babel: Random Sampling as a Strong Baseline for Prompt OptimisationCode0
Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring0
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination0
Crafting In-context Examples according to LMs' Parametric KnowledgeCode0
HuatuoGPT-II, One-stage Training for Medical Adaption of LLMsCode2
On Retrieval Augmentation and the Limitations of Language Model Training0
WatME: Towards Lossless Watermarking Through Lexical Redundancy0
Reducing Privacy Risks in Online Self-Disclosures with Language Models0
Multi-Step Dialogue Workflow Action Prediction0
A Speed Odyssey for Deployable Quantization of LLMs0
Video-LLaVA: Learning United Visual Representation by Alignment Before ProjectionCode4
Leveraging LLMs in Scholarly Knowledge Graph Question AnsweringCode0
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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