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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9501–9550 of 17610 papers

TitleStatusHype
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation—0
LLM-FuncMapper: Function Identification for Interpreting Complex Clauses in Building Codes via LLM—0
LLM-Gomoku: A Large Language Model-Based System for Strategic Gomoku with Self-Play and Reinforcement Learning—0
LLM-grounded Video Diffusion Models—0
LLMic: Romanian Foundation Language Model—0
LLMIdxAdvis: Resource-Efficient Index Advisor Utilizing Large Language Model—0
LLM in a flash: Efficient Large Language Model Inference with Limited Memory—0
LLM Inference Serving: Survey of Recent Advances and Opportunities—0
LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering—0
LLM-mediated Dynamic Plan Generation with a Multi-Agent Approach—0
LLM-Mediated Guidance of MARL Systems—0
LLM-Mini-CEX: Automatic Evaluation of Large Language Model for Diagnostic Conversation—0
LLM-ODDR: A Large Language Model Framework for Joint Order Dispatching and Driver Repositioning—0
LLM-PCGC: Large Language Model-based Point Cloud Geometry Compression—0
LLM-POET: Evolving Complex Environments using Large Language Models—0
LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward—0
LLM Pretraining with Continuous Concepts—0
LLM Questionnaire Completion for Automatic Psychiatric Assessment—0
LLMRA: Multi-modal Large Language Model based Restoration Assistant—0
LLMR: Knowledge Distillation with a Large Language Model-Induced Reward—0
LLMR: Real-time Prompting of Interactive Worlds using Large Language Models—0
LLMs are Good Action Recognizers—0
LLMs are Superior Feedback Providers: Bootstrapping Reasoning for Lie Detection with Self-Generated Feedback—0
LLMs as Narcissistic Evaluators: When Ego Inflates Evaluation Scores—0
LLM-SEM: A Sentiment-Based Student Engagement Metric Using LLMS for E-Learning Platforms—0
LLM should think and action as a human—0
LLMs in Coding and their Impact on the Commercial Software Engineering Landscape—0
LLMs left, right, and center: Assessing GPT's capabilities to label political bias from web domains—0
LLMs meet Federated Learning for Scalable and Secure IoT Management—0
LLM Social Simulations Are a Promising Research Method—0
LLMs + Persona-Plug = Personalized LLMs—0
LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model—0
LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems—0
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model—0
LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computation—0
LLM-USO: Large Language Model-based Universal Sizing Optimizer—0
LLM-VPRF: Large Language Model Based Vector Pseudo Relevance Feedback—0
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model—0
LLM Watermarking Using Mixtures and Statistical-to-Computational Gaps—0
LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs—0
LLplace: The 3D Indoor Scene Layout Generation and Editing via Large Language Model—0
LLV-FSR: Exploiting Large Language-Vision Prior for Face Super-resolution—0
LM4HPC: Towards Effective Language Model Application in High-Performance Computing—0
LM-assisted keyword biasing with Aho-Corasick algorithm for Transducer-based ASR—0
LMCanvas: Object-Oriented Interaction to Personalize Large Language Model-Powered Writing Environments—0
LM-Cocktail: Resilient Tuning of Language Models via Model Merging—0
LMD3: Language Model Data Density Dependence—0
LMDX: Language Model-based Document Information Extraction and Localization—0
LMGQS: A Large-scale Dataset for Query-focused Summarization—0
Reward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework—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