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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9351–9400 of 17610 papers

TitleStatusHype
Analyzing the Roles of Language and Vision in Learning from Limited Data—0
Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4—0
A Language Model for Particle Tracking—0
Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies—0
AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systems—0
Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications—0
FGeo-TP: A Language Model-Enhanced Solver for Geometry Problems—0
FGeo-DRL: Deductive Reasoning for Geometric Problems through Deep Reinforcement LearningCode0
Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model—0
Large Language Model with Graph Convolution for Recommendation—0
Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-raysCode0
Multi-Query Focused Disaster Summarization via Instruction-Based Prompting—0
Large Language Model Simulator for Cold-Start Recommendation—0
Large Language Model-Based Interpretable Machine Learning Control in Building Energy Systems—0
Rethinking Large Language Model Architectures for Sequential Recommendations—0
AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and GuardrailsCode0
Privacy-Preserving Language Model Inference with Instance Obfuscation—0
The Application of ChatGPT in Responding to Questions Related to the Boston Bowel Preparation Scale—0
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill—0
Punctuation Restoration Improves Structure Understanding Without SupervisionCode0
Visually Dehallucinative Instruction GenerationCode0
Visual Question Answering Instruction: Unlocking Multimodal Large Language Model To Domain-Specific Visual Multitasks—0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs—0
Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User QueriesCode0
LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges—0
Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models—0
Game Agent Driven by Free-Form Text Command: Using LLM-based Code Generation and Behavior Branch—0
Active Preference Learning for Large Language Models—0
Detecting the Clinical Features of Difficult-to-Treat Depression using Synthetic Data from Large Language ModelsCode0
Enhancing Multi-Criteria Decision Analysis with AI: Integrating Analytic Hierarchy Process and GPT-4 for Automated Decision Support—0
Differentially Private Zeroth-Order Methods for Scalable Large Language Model Finetuning—0
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT—0
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model—0
Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets—0
Assessing Generalization for Subpopulation Representative Modeling via In-Context Learning—0
Careless Whisper: Speech-to-Text Hallucination HarmsCode0
Lumos : Empowering Multimodal LLMs with Scene Text Recognition—0
SemTra: A Semantic Skill Translator for Cross-Domain Zero-Shot Policy Adaptation—0
Suppressing Pink Elephants with Direct Principle Feedback—0
MAFIA: Multi-Adapter Fused Inclusive LanguAge Models—0
Pushing The Limit of LLM Capacity for Text Classification—0
Why and When LLM-Based Assistants Can Go Wrong: Investigating the Effectiveness of Prompt-Based Interactions for Software Help-Seeking—0
Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science EducationCode0
Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine—0
Effort and Size Estimation in Software Projects with Large Language Model-based Intelligent Interfaces—0
CPSDBench: A Large Language Model Evaluation Benchmark and Baseline for Chinese Public Security Domain—0
Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?—0
TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation—0
Large-Language-Model Empowered Dose Volume Histogram Prediction for Intensity Modulated Radiotherapy—0
REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language ModelsCode0
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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