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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 5051–5100 of 17610 papers

TitleStatusHype
PANDORA: Diffusion Policy Learning for Dexterous Robotic Piano Playing—0
Agents Play Thousands of 3D Video Games—0
High-entropy Advantage in Neural Networks' Generalizability—0
HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model—0
Analytic Subspace Routing: How Recursive Least Squares Works in Continual Learning of Large Language Model—0
HybridGen: VLM-Guided Hybrid Planning for Scalable Data Generation of Imitation Learning—0
Valid Text-to-SQL Generation with Unification-based DeepStochLogCode0
State Fourier Diffusion Language Model (SFDLM): A Scalable, Novel Iterative Approach to Language Modeling—0
LLM-Mediated Guidance of MARL Systems—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
Interpretation Gaps in LLM-Assisted Comprehension of Privacy Documents—0
Applications of Large Language Model Reasoning in Feature Generation—0
Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language ModelsCode0
Research on Large Language Model Cross-Cloud Privacy Protection and Collaborative Training based on Federated Learning—0
Maritime Mission Planning for Unmanned Surface Vessel using Large Language Model—0
Tailor: An Integrated Text-Driven CG-Ready Human and Garment Generation System—0
Potential of large language model-powered nudges for promoting daily water and energy conservation—0
Rule-Guided Feedback: Enhancing Reasoning by Enforcing Rule Adherence in Large Language Models—0
Large language model-powered AI systems achieve self-replication with no human intervention—0
Text Compression for Efficient Language Generation—0
LLM Agents for Education: Advances and Applications—0
Towards Extreme Pruning of LLMs with Plug-and-Play Mixed Sparsity—0
TigerLLM -- A Family of Bangla Large Language ModelsCode0
Test-Time Training Provably Improves Transformers as In-context Learners—0
Reasoning-Grounded Natural Language Explanations for Language ModelsCode0
BriLLM: Brain-inspired Large Language Model—0
ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction TuningCode0
Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models—0
Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning—0
Hybrid Agents for Image Restoration—0
Representation-based Reward Modeling for Efficient Safety Alignment of Large Language Model—0
SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable—0
NeurIPS 2023 LLM Efficiency Fine-tuning Competition—0
PRISM: Preference Refinement via Implicit Scene Modeling for 3D Vision-Language Preference-Based Reinforcement Learning—0
Tempest: Autonomous Multi-Turn Jailbreaking of Large Language Models with Tree Search—0
TacticExpert: Spatial-Temporal Graph Language Model for Basketball Tactics—0
LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems—0
Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More—0
MouseGPT: A Large-scale Vision-Language Model for Mouse Behavior Analysis—0
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation—0
SmartWay: Enhanced Waypoint Prediction and Backtracking for Zero-Shot Vision-and-Language Navigation—0
Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity—0
Leveraging Knowledge Graphs and LLMs for Context-Aware Messaging—0
Token Weighting for Long-Range Language ModelingCode0
PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs—0
Sometimes Painful but Certainly Promising: Feasibility and Trade-offs of Language Model Inference at the Edge—0
SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability—0
Reinforcement Learning is all You Need—0
Language-Enhanced Representation Learning for Single-Cell TranscriptomicsCode0
NVP-HRI: Zero Shot Natural Voice and Posture-based Human-Robot Interaction via Large Language ModelCode0
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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