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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9751–9800 of 17610 papers

TitleStatusHype
Searching, fast and slow, through product catalogs—0
Querying as Prompt: Parameter-Efficient Learning for Multimodal Language Model—0
Large Language Models aren't all that you need—0
Predicting Anti-microbial Resistance using Large Language Models—0
Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education—0
Large language model for Bible sentiment analysis: Sermon on the MountCode0
Revisiting Counterfactual Problems in Referring Expression ComprehensionCode0
PeVL: Pose-Enhanced Vision-Language Model for Fine-Grained Human Action Recognition—0
On Scaling Up a Multilingual Vision and Language Model—0
Neural Networks Against (and For) Self-Training: Classification with Small Labeled and Large Unlabeled SetsCode0
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws—0
Bidirectional Trained Tree-Structured Decoder for Handwritten Mathematical Expression Recognition—0
DocLLM: A layout-aware generative language model for multimodal document understanding—0
HSC-GPT: A Large Language Model for Human Settlements Construction—0
Boosting Large Language Model for Speech Synthesis: An Empirical Study—0
ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge GraphCode0
Trace and Edit Relation Associations in GPT—0
Principled Gradient-based Markov Chain Monte Carlo for Text Generation—0
State Machine of Thoughts: Leveraging Past Reasoning Trajectories for Enhancing Problem Solving—0
Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning—0
Do Androids Know They're Only Dreaming of Electric Sheep?—0
How Far Are LLMs from Believable AI? A Benchmark for Evaluating the Believability of Human Behavior SimulationCode0
Virtual Scientific Companion for Synchrotron Beamlines: A Prototype—0
Learning to Generate Text in Arbitrary Writing Styles—0
LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model—0
Spike No More: Stabilizing the Pre-training of Large Language Models—0
Language Model as an Annotator: Unsupervised Context-aware Quality Phrase Generation—0
On the rate of convergence of an over-parametrized Transformer classifier learned by gradient descent—0
Towards Auto-Modeling of Formal Verification for NextG Protocols: A Multimodal cross- and self-attention Large Language Model Approach—0
PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation—0
Exploring intra-task relations to improve meta-learning algorithms—0
Automating Knowledge Acquisition for Content-Centric Cognitive Agents Using LLMs—0
A Large Language Model-based Computational Approach to Improve Identity-Related Write-Ups—0
A bi-objective ε-constrained framework for quality-cost optimization in language model ensembles—0
KnowledgeNavigator: Leveraging Large Language Models for Enhanced Reasoning over Knowledge Graph—0
PersianLLaMA: Towards Building First Persian Large Language Model—0
Preliminary Study on Incremental Learning for Large Language Model-based Recommender SystemsCode0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
A Split-and-Privatize Framework for Large Language Model Fine-Tuning—0
Fairness-Aware Structured Pruning in TransformersCode0
Multimodal Classification of Teaching Activities from University Lecture Recordings—0
ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation—0
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems—0
Paralinguistics-Enhanced Large Language Modeling of Spoken Dialogue—0
An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development—0
Empowering Working Memory for Large Language Model Agents—0
Assessing the Impact of Prompting Methods on ChatGPT's Mathematical Capabilities—0
Personalized Large Language Model Assistant with Evolving Conditional Memory—0
Revisiting Few-Shot Object Detection with Vision-Language ModelsCode0
Language Model is a Branch Predictor for Simultaneous Machine TranslationCode0
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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