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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7951–8000 of 17610 papers

TitleStatusHype
Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization—0
Reframing linguistic bootstrapping as joint inference using visually-grounded grammar induction modelsCode0
Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression—0
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels—0
STEVE Series: Step-by-Step Construction of Agent Systems in Minecraft—0
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference ContentCode0
Self-training Large Language Models through Knowledge DetectionCode0
Self-Train Before You TranscribeCode0
A General Framework for Load Forecasting based on Pre-trained Large Language Model—0
Skip-Layer Attention: Bridging Abstract and Detailed Dependencies in Transformers—0
LiLiuM: eBay's Large Language Models for e-commerce—0
Retrieval-Augmented Feature Generation for Domain-Specific Classification—0
Promises, Outlooks and Challenges of Diffusion Language Modeling—0
Reminding Multimodal Large Language Models of Object-aware Knowledge with Retrieved Tags—0
ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank AdaptationCode0
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuningCode0
Large Language Models for Dysfluency Detection in Stuttered Speech—0
Logit Separability-Driven Samples and Multiple Class-Related Words Selection for Advancing In-Context LearningCode0
Balancing Rigor and Utility: Mitigating Cognitive Biases in Large Language Models for Multiple-Choice QuestionsCode0
Optimization of Armv9 architecture general large language model inference performance based on Llama.cppCode0
Taking a Deep Breath: Enhancing Language Modeling of Large Language Models with Sentinel Tokens—0
WundtGPT: Shaping Large Language Models To Be An Empathetic, Proactive Psychologist—0
CrisisSense-LLM: Instruction Fine-Tuned Large Language Model for Multi-label Social Media Text Classification in Disaster InformaticsCode0
City-LEO: Toward Transparent City Management Using LLM with End-to-End Optimization—0
Avoiding Copyright Infringement via Large Language Model UnlearningCode0
Augmenting Biomedical Named Entity Recognition with General-domain ResourcesCode0
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models—0
Intertwining CP and NLP: The Generation of Unreasonably Constrained Sentences—0
CancerLLM: A Large Language Model in Cancer Domain—0
Reactor Mk.1 performances: MMLU, HumanEval and BBH test results—0
RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics—0
Spuriousness-Aware Meta-Learning for Learning Robust ClassifiersCode0
Mental Disorder Classification via Temporal Representation of Text—0
Large Language Model Enhanced Clustering for News Event Detection—0
Task Facet Learning: A Structured Approach to Prompt Optimization—0
MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data—0
VCEval: Rethinking What is a Good Educational Video and How to Automatically Evaluate It—0
Vision Language Modeling of Content, Distortion and Appearance for Image Quality Assessment—0
UniBridge: A Unified Approach to Cross-Lingual Transfer Learning for Low-Resource LanguagesCode0
A Probability--Quality Trade-off in Aligned Language Models and its Relation to Sampling Adaptors—0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
3D-RPE: Enhancing Long-Context Modeling Through 3D Rotary Position Encoding—0
Datasets for Multilingual Answer Sentence Selection—0
GEB-1.3B: Open Lightweight Large Language Model—0
TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners—0
Let the Poem Hit the Rhythm: Using a Byte-Based Transformer for Beat-Aligned Poetry GenerationCode0
PRISM: A Design Framework for Open-Source Foundation Model Safety—0
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models—0
RoboGolf: Mastering Real-World Minigolf with a Reflective Multi-Modality Vision-Language Model—0
OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst—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