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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 5501–5550 of 17610 papers

TitleStatusHype
Semantic Gesticulator: Semantics-Aware Co-Speech Gesture SynthesisCode3
Generative Design through Quality-Diversity Data Synthesis and Language Models—0
Enhancing Maritime Trajectory Forecasting via H3 Index and Causal Language Modelling (CLM)—0
Spectral Editing of Activations for Large Language Model AlignmentCode1
New Textual Corpora for Serbian Language Modeling—0
HAAP: Vision-context Hierarchical Attention Autoregressive with Adaptive Permutation for Scene Text Recognition—0
Large Language Model Bias Mitigation from the Perspective of Knowledge Editing—0
Word Alignment as Preference for Machine Translation—0
Xmodel-VLM: A Simple Baseline for Multimodal Vision Language ModelCode2
Assisted Debate Builder with Large Language Models—0
QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models—0
Automated Repair of AI Code with Large Language Models and Formal Verification—0
Contextual Emotion Recognition using Large Vision Language Models—0
Incorporating Clinical Guidelines through Adapting Multi-modal Large Language Model for Prostate Cancer PI-RADS ScoringCode1
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese UnderstandingCode7
Improving Transformers with Dynamically Composable Multi-Head AttentionCode3
Thinking Tokens for Language Modeling—0
Understanding the performance gap between online and offline alignment algorithms—0
SpeechVerse: A Large-scale Generalizable Audio Language Model—0
Distributed Threat Intelligence at the Edge Devices: A Large Language Model-Driven Approach—0
Self-Distillation Improves DNA Sequence InferenceCode0
News Recommendation with Category Description by a Large Language ModelCode0
UCCIX: Irish-eXcellence Large Language Model—0
From Questions to Insightful Answers: Building an Informed Chatbot for University Resources—0
Layout Generation Agents with Large Language ModelsCode0
Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-RankingCode1
The Curious Case of Class Accuracy Imbalance in LLMs: Post-hoc Debiasing via Nonlinear Integer Programming—0
Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT—0
Age-Dependent Analysis and Stochastic Generation of Child-Directed SpeechCode0
ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source—0
Many-Shot Regurgitation (MSR) Prompting—0
RLHF Workflow: From Reward Modeling to Online RLHFCode5
A Generalist Learner for Multifaceted Medical Image Interpretation—0
PromptLink: Leveraging Large Language Models for Cross-Source Biomedical Concept LinkingCode1
Strategic Data Ordering: Enhancing Large Language Model Performance through Curriculum Learning—0
Understanding Sarcoidosis Using Large Language Models and Social Media Data—0
Counting Clinical Trials: New Evidence on Pharmaceutical Sector Productivity—0
ExplainableDetector: Exploring Transformer-based Language Modeling Approach for SMS Spam Detection with Explainability Analysis—0
Post Training Quantization of Large Language Models with Microscaling Formats—0
Edge Intelligence Optimization for Large Language Model Inference with Batching and Quantization—0
DiffGen: Robot Demonstration Generation via Differentiable Physics Simulation, Differentiable Rendering, and Vision-Language Model—0
Differentiable Model Scaling using Differentiable TopkCode1
Large Language Model-aided Edge Learning in Distribution System State Estimation—0
Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPTCode0
Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA—0
Improving Targeted Molecule Generation through Language Model Fine-Tuning Via Reinforcement Learning—0
Large Language Model in Financial Regulatory Interpretation—0
SaudiBERT: A Large Language Model Pretrained on Saudi Dialect CorporaCode0
PLeak: Prompt Leaking Attacks against Large Language Model ApplicationsCode2
CANAL -- Cyber Activity News Alerting Language Model: Empirical Approach vs. Expensive LLM—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