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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7251–7300 of 17610 papers

TitleStatusHype
Large Language Model Driven Recommendation—0
MEGen: Generative Backdoor in Large Language Models via Model Editing—0
Predicting Rewards Alongside Tokens: Non-disruptive Parameter Insertion for Efficient Inference Intervention in Large Language ModelCode0
Hide Your Malicious Goal Into Benign Narratives: Jailbreak Large Language Models through Carrier Articles—0
ColBERT Retrieval and Ensemble Response Scoring for Language Model Question AnsweringCode0
HMoE: Heterogeneous Mixture of Experts for Language Modeling—0
Analysis of Plan-based Retrieval for Grounded Text Generation—0
Data Augmentation Integrating Dialogue Flow and Style to Adapt Spoken Dialogue Systems to Low-Resource User Groups—0
Fine-Tuning a Local LLaMA-3 Large Language Model for Automated Privacy-Preserving Physician Letter Generation in Radiation Oncology—0
CTP-LLM: Clinical Trial Phase Transition Prediction Using Large Language Models—0
Beyond Relevant Documents: A Knowledge-Intensive Approach for Query-Focused Summarization using Large Language Models—0
BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction—0
Cross-composition Feature Disentanglement for Compositional Zero-shot Learning—0
A Comparison of Large Language Model and Human Performance on Random Number Generation TasksCode0
Development of an AI Anti-Bullying System Using Large Language Model Key Topic Detection—0
IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and AbductionCode0
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts—0
AutoML-guided Fusion of Entity and LLM-based Representations for Document ClassificationCode0
Geometry Informed Tokenization of Molecules for Language Model Generation—0
Importance Weighting Can Help Large Language Models Self-ImproveCode0
Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework—0
MSDiagnosis: A Benchmark for Evaluating Large Language Models in Multi-Step Clinical Diagnosis—0
MoDeGPT: Modular Decomposition for Large Language Model Compression—0
MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation—0
R2GenCSR: Retrieving Context Samples for Large Language Model based X-ray Medical Report Generation—0
SSDTrain: An Activation Offloading Framework to SSDs for Faster Large Language Model Training—0
Minor DPO reject penalty to increase training robustness—0
MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model—0
Self-Refined Generative Foundation Models for Wireless Traffic Prediction—0
REFINE-LM: Mitigating Language Model Stereotypes via Reinforcement Learning—0
Moonshine: Distilling Game Content Generators into Steerable Generative Models—0
PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis—0
Grammatical Error Feedback: An Implicit Evaluation Approach—0
FASST: Fast LLM-based Simultaneous Speech Translation—0
Crossing New Frontiers: Knowledge-Augmented Large Language Model Prompting for Zero-Shot Text-Based De Novo Molecule Design—0
Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech RecognitionCode0
AI Managed Emergency Documentation with a Pretrained Model—0
Architectural Foundations for the Large Language Model Infrastructures—0
Chinese Metaphor Recognition Using a Multi-stage Prompting Large Language Model—0
CogLM: Tracking Cognitive Development of Large Language Models—0
Sentiment analysis of preservice teachers' reflections using a large language model—0
Risks and NLP Design: A Case Study on Procedural Document QA—0
LLM-PCGC: Large Language Model-based Point Cloud Geometry Compression—0
Research on Personalized Compression Algorithm for Pre-trained Models Based on Homomorphic Entropy Increase—0
Quantifying the Effectiveness of Student Organization Activities using Natural Language Processing—0
CIKMar: A Dual-Encoder Approach to Prompt-Based Reranking in Educational Dialogue Systems—0
Improving VTE Identification through Language Models from Radiology Reports: A Comparative Study of Mamba, Phi-3 Mini, and BERT—0
ASGM-KG: Unveiling Alluvial Gold Mining Through Knowledge Graphs—0
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs—0
An End-to-End Model for Photo-Sharing Multi-modal Dialogue GenerationCode0
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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