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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 11901–11950 of 17610 papers

TitleStatusHype
User Persona Identification and New Service Adaptation Recommendation—0
UserLibri: A Dataset for ASR Personalization Using Only Text—0
VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration—0
VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection—0
User Intent to Use DeepSeek for Healthcare Purposes and their Trust in the Large Language Model: Multinational Survey Study—0
User Edits Classification Using Document Revision Histories—0
User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning—0
VLLFL: A Vision-Language Model Based Lightweight Federated Learning Framework for Smart Agriculture—0
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks—0
VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision—0
VLMAE: Vision-Language Masked Autoencoder—0
VL-Mamba: Exploring State Space Models for Multimodal Learning—0
VLMaterial: Procedural Material Generation with Large Vision-Language Models—0
VLM-HOI: Vision Language Models for Interpretable Human-Object Interaction Analysis—0
VLMine: Long-Tail Data Mining with Vision Language Models—0
VLM-KD: Knowledge Distillation from VLM for Long-Tail Visual Recognition—0
VLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection via Vision-Language Model—0
Use of probabilistic phrases in a coordination game: human versus GPT-4—0
VLM-RRT: Vision Language Model Guided RRT Search for Autonomous UAV Navigation—0
VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model—0
VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding—0
VLN-Video: Utilizing Driving Videos for Outdoor Vision-and-Language Navigation—0
Use of Knowledge Graph in Rescoring the N-Best List in Automatic Speech Recognition—0
URL-BERT: Training Webpage Representations via Social Media Engagements—0
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension—0
EVJVQA Challenge: Multilingual Visual Question Answering—0
Unintended Bias in Language Model-driven Conversational Recommendation—0
UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion—0
VMAD: Visual-enhanced Multimodal Large Language Model for Zero-Shot Anomaly Detection—0
URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors—0
Vocabulary Attack to Hijack Large Language Model Applications—0
Urdu News Article Recommendation Model using Natural Language Processing Techniques—0
Unigram-Normalized Perplexity as a Language Model Performance Measure with Different Vocabulary Sizes—0
VocalAgent: Large Language Models for Vocal Health Diagnostics with Safety-Aware Evaluation—0
UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models—0
Urban Air Mobility as a System of Systems: An LLM-Enhanced Holonic Approach—0
UQAM-NTL: Named entity recognition in Twitter messages—0
UPM system for WMT 2012—0
VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Tasks—0
Voltron: A Hybrid System For Answer Validation Based On Lexical And Distance Features—0
VoroNav: Voronoi-based Zero-shot Object Navigation with Large Language Model—0
UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation—0
VoxRep: Enhancing 3D Spatial Understanding in 2D Vision-Language Models via Voxel Representation—0
Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks—0
VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving—0
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models—0
VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits—0
UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation—0
VQ-T: RNN Transducers using Vector-Quantized Prediction Network States—0
VR-GPT: Visual Language Model for Intelligent Virtual Reality Applications—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