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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 85518600 of 17610 papers

TitleStatusHype
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction0
PromptCL: Improving Event Representation via Prompt Template and Contrastive LearningCode0
Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal0
VANER: Leveraging Large Language Model for Versatile and Adaptive Biomedical Named Entity Recognition0
CEval: A Benchmark for Evaluating Counterfactual Text GenerationCode0
Ruffle&Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System0
Large Language Model Agent as a Mechanical Designer0
The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances0
Player-Driven Emergence in LLM-Driven Game Narrative0
Tele-FLM Technical Report0
Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model0
Learning Syntax Without Planting Trees: Understanding When and Why Transformers Generalize HierarchicallyCode0
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites0
Influence of Solution Efficiency and Valence of Instruction on Additive and Subtractive Solution Strategies in Humans and GPT-40
Evaluating Class Membership Relations in Knowledge Graphs using Large Language ModelsCode0
Detecting Conceptual Abstraction in LLMs0
Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering0
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search0
Generalization Measures for Zero-Shot Cross-Lingual Transfer0
Can Foundational Large Language Models Assist with Conducting Pharmaceuticals Manufacturing Investigations?0
Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering0
A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industry0
Attacks on Third-Party APIs of Large Language ModelsCode0
Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses0
CORM: Cache Optimization with Recent Message for Large Language Model Inference0
Knowledge Graph Completion using Structural and Textual EmbeddingsCode0
Towards Efficient Patient Recruitment for Clinical Trials: Application of a Prompt-Based Learning Model0
Re-Thinking Inverse Graphics With Large Language Models0
Retrieval Augmented Generation for Domain-specific Question Answering0
Pegasus-v1 Technical Report0
From Complexity to Clarity: How AI Enhances Perceptions of Scientists and the Public's Understanding of Science0
Pushing the Boundaries of Text to Motion with Arbitrary Text: A New Task0
Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning0
RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model0
Multimodal Large Language Model is a Human-Aligned Annotator for Text-to-Image Generation0
Detection of circular permutations by Protein Language ModelsCode0
ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning0
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation0
Breaking Walls: Pioneering Automatic Speech Recognition for Central Kurdish: End-to-End Transformer Paradigm0
XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference0
Visual Delta Generator with Large Multi-modal Models for Semi-supervised Composed Image Retrieval0
WangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction0
Understanding the role of FFNs in driving multilingual behaviour in LLMs0
PARAMANU-GANITA: Language Model with Mathematical Capabilities0
Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning0
Pixels and Predictions: Potential of GPT-4V in Meteorological Imagery Analysis and Forecast Communication0
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone0
From LLM to NMT: Advancing Low-Resource Machine Translation with Claude0
Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question AnsweringCode0
A Multimodal Automated Interpretability Agent0
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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