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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 10701–10750 of 17610 papers

TitleStatusHype
AMuRD: Annotated Arabic-English Receipt Dataset for Key Information Extraction and ClassificationCode0
Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decoding—0
From Cooking Recipes to Robot Task Trees -- Improving Planning Correctness and Task Efficiency by Leveraging LLMs with a Knowledge Network—0
A novel approach to measuring the scope of patent claims based on probabilities obtained from (large) language models—0
Do Large GPT Models Discover Moral Dimensions in Language Representations? A Topological Study Of Sentence Embeddings—0
Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model—0
Performance of the Pre-Trained Large Language Model GPT-4 on Automated Short Answer Grading—0
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs—0
Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals—0
Vocabulary-level Memory Efficiency for Language Model Fine-tuningCode0
Compositional Foundation Models for Hierarchical Planning—0
Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language ModelsCode0
BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials—0
Enhance audio generation controllability through representation similarity regularization—0
Using Large Language Model to Solve and Explain Physics Word Problems Approaching Human Level—0
VulnSense: Efficient Vulnerability Detection in Ethereum Smart Contracts by Multimodal Learning with Graph Neural Network and Language Model—0
Self-Consistent Narrative Prompts on Abductive Natural Language InferenceCode0
Towards Practical and Efficient Image-to-Speech Captioning with Vision-Language Pre-training and Multi-modal Tokens—0
Structural Self-Supervised Objectives for TransformersCode0
t-SOT FNT: Streaming Multi-talker ASR with Text-only Domain Adaptation Capability—0
MAPLE: Mobile App Prediction Leveraging Large Language Model EmbeddingsCode0
Neural Machine Translation Models Can Learn to be Few-shot Learners—0
Stack-and-Delay: a new codebook pattern for music generation—0
Masked Diffusion with Task-awareness for Procedure Planning in Instructional VideosCode0
PerPLM: Personalized Fine-tuning of Pretrained Language Models via Writer-specific Intermediate Learning and Prompts—0
Text Classification of Cancer Clinical Trial Eligibility Criteria—0
Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer—0
Leveraging Contextual Information for Effective Entity Salience Detection—0
Hybrid Attention-based Encoder-decoder Model for Efficient Language Model Adaptation—0
Incorporating Class-based Language Model for Named Entity Recognition in Factorized Neural Transducer—0
Anchor Points: Benchmarking Models with Much Fewer ExamplesCode0
A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender SystemsCode0
Generative AI Text Classification using Ensemble LLM Approaches—0
Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Text—0
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?—0
Computer says 'no': Exploring systemic bias in ChatGPT using an audit approach—0
ChatGPT v Bard v Bing v Claude 2 v Aria v human-expert. How good are AI chatbots at scientific writing?—0
Advancing Regular Language Reasoning in Linear Recurrent Neural NetworksCode0
Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks—0
Unsupervised Contrast-Consistent Ranking with Language ModelsCode0
Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion EnhancementCode0
Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in RoboticsCode0
Statistical Rejection Sampling Improves Preference Optimization—0
Recovering from Privacy-Preserving Masking with Large Language Models—0
Narrowing the Gap between Supervised and Unsupervised Sentence Representation Learning with Large Language ModelCode0
Leveraging Large Language Models for Automated Dialogue AnalysisCode0
Characterizing Latent Perspectives of Media Houses Towards Public Figures—0
AstroLLaMA: Towards Specialized Foundation Models in Astronomy—0
Improving Robustness of Neural Inverse Text Normalization via Data-Augmentation, Semi-Supervised Learning, and Post-Aligning Method—0
Do Generative Large Language Models need billions of parameters?—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