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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9551–9600 of 17610 papers

TitleStatusHype
LLM4SecHW: Leveraging Domain Specific Large Language Model for Hardware Debugging—0
Dynamically Allocated Interval-Based Generative Linguistic Steganography with Roulette WheelCode0
PRE: A Peer Review Based Large Language Model Evaluator—0
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation—0
Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately—0
Equipping Language Models with Tool Use Capability for Tabular Data Analysis in Finance—0
Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain Specific Knowledge—0
An Empirical Investigation of Domain Adaptation Ability for Chinese Spelling Check Models—0
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement LearningCode0
Measuring Moral Inconsistencies in Large Language Models—0
MaLLaM -- Malaysia Large Language Model—0
Turn-taking and Backchannel Prediction with Acoustic and Large Language Model Fusion—0
Spatial Transcriptomics Analysis of Zero-shot Gene Expression Prediction—0
Query of CC: Unearthing Large Scale Domain-Specific Knowledge from Public Corpora—0
Large Language Model Adaptation for Financial Sentiment Analysis—0
Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection—0
Language Modelling Approaches to Adaptive Machine Translation—0
MULTIVERSE: Exposing Large Language Model Alignment Problems in Diverse Worlds—0
StyleInject: Parameter Efficient Tuning of Text-to-Image Diffusion Models—0
The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support—0
LocMoE: A Low-Overhead MoE for Large Language Model Training—0
Looking Right is Sometimes Right: Investigating the Capabilities of Decoder-only LLMs for Sequence Labeling—0
Hierarchical Continual Reinforcement Learning via Large Language Model—0
Accelerating Retrieval-Augmented Language Model Serving with Speculation—0
Improving Natural Language Capability of Code Large Language ModelCode0
ChatGPT vs Gemini vs LLaMA on Multilingual Sentiment Analysis—0
Embedding Attack Project (Work Report)—0
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification—0
How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment—0
A Unified Approach to Emotion Detection and Task-Oriented Dialogue ModelingCode0
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?Code0
It's About Time: Incorporating Temporality in Retrieval Augmented Language Models—0
MLLMReID: Multimodal Large Language Model-based Person Re-identification—0
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data—0
Supporting Sensemaking of Large Language Model Outputs at Scale—0
MambaByte: Token-free Selective State Space Model—0
MaLA-500: Massive Language Adaptation of Large Language Models—0
Large language model empowered participatory urban planning—0
Large Malaysian Language Model Based on Mistral for Enhanced Local Language Understanding—0
TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidance—0
LPNL: Scalable Link Prediction with Large Language Models—0
UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion—0
XAI for All: Can Large Language Models Simplify Explainable AI?—0
Training-Free Action Recognition and Goal Inference with Dynamic Frame Selection—0
Assessing and Understanding Creativity in Large Language Models—0
ChatGraph: Chat with Your Graphs—0
Generating Zero-shot Abstractive Explanations for Rumour VerificationCode0
Comparing Pre-trained Human Language Models: Is it Better with Human Context as Groups, Individual Traits, or Both?—0
Eloquent: A More Robust Transmission Scheme for LLM Token Streaming—0
Multilingual and Fully Non-Autoregressive ASR with Large Language Model Fusion: A Comprehensive Study—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