SOTAVerified

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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 8951–9000 of 17610 papers

TitleStatusHype
Exosense: A Vision-Based Scene Understanding System For Exoskeletons—0
Editing Knowledge Representation of Language Model via Rephrased Prefix Prompts—0
PE-GPT: A Physics-Informed Interactive Large Language Model for Power Converter Modulation Design—0
Leveraging Large Language Model-based Room-Object Relationships Knowledge for Enhancing Multimodal-Input Object Goal Navigation—0
MyVLM: Personalizing VLMs for User-Specific Queries—0
Locating and Mitigating Gender Bias in Large Language Models—0
Sequential Decision-Making for Inline Text Autocomplete—0
PeerGPT: Probing the Roles of LLM-based Peer Agents as Team Moderators and Participants in Children's Collaborative Learning—0
LLM-based Extraction of Contradictions from Patents—0
Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural NetworkCode0
LayoutLLM: Large Language Model Instruction Tuning for Visually Rich Document Understanding—0
Sequence-to-Sequence Language Models for Character and Emotion Detection in Dream Narratives—0
Recourse for reclamation: Chatting with generative language models—0
VidLA: Video-Language Alignment at Scale—0
VL-Mamba: Exploring State Space Models for Multimodal Learning—0
Vi-Mistral-X: Building a Vietnamese Language Model with Advanced Continual Pre-training—0
VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model—0
Bridge the Modality and Capability Gaps in Vision-Language Model Selection—0
Different Tokenization Schemes Lead to Comparable Performance in Spanish Number Agreement—0
Enhancing Traffic Incident Management with Large Language Models: A Hybrid Machine Learning Approach for Severity Classification—0
Hyacinth6B: A large language model for Traditional Chinese—0
Community Needs and Assets: A Computational Analysis of Community ConversationsCode0
A New Massive Multilingual Dataset for High-Performance Language Technologies—0
Enhancing Gait Video Analysis in Neurodegenerative Diseases by Knowledge Augmentation in Vision Language Model—0
Train & Constrain: Phonologically Informed Tongue-Twister Generation from Topics and Paraphrases—0
Reducing Large Language Model Bias with Emphasis on 'Restricted Industries': Automated Dataset Augmentation and Prejudice Quantification—0
SumTra: A Differentiable Pipeline for Few-Shot Cross-Lingual SummarizationCode0
LaPuda: LLM-Enabled Policy-Based Query Optimizer for Multi-modal Data—0
PARAMANU-AYN: Pretrain from scratch or Continual Pretraining of LLMs for Legal Domain Adaptation?—0
Out-of-Distribution Detection Using Peer-Class Generated by Large Language Model—0
Learning from Synthetic Data for Visual Grounding—0
Towards Interpretable Hate Speech Detection using Large Language Model-extracted RationalesCode0
Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference—0
SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model—0
MSLM-S2ST: A Multitask Speech Language Model for Textless Speech-to-Speech Translation with Speaker Style Preservation—0
Third-Party Language Model Performance Prediction from InstructionCode0
RelationVLM: Making Large Vision-Language Models Understand Visual Relations—0
MEDBind: Unifying Language and Multimodal Medical Data Embeddings—0
Towards Multimodal In-Context Learning for Vision & Language Models—0
LLM-GEm: Large Language Model-Guided Prediction of People’s Empathy Levels towards Newspaper ArticleCode0
WoLF: Wide-scope Large Language Model Framework for CXR Understanding—0
AraPoemBERT: A Pretrained Language Model for Arabic Poetry Analysis—0
CrossTune: Black-Box Few-Shot Classification with Label Enhancement—0
Bypassing LLM Watermarks with Color-Aware Substitutions—0
Automatic Information Extraction From Employment Tribunal Judgements Using Large Language Models—0
Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization—0
Automated Data Curation for Robust Language Model Fine-Tuning—0
Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning—0
FlexCap: Describe Anything in Images in Controllable Detail—0
Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting PotCode0
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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