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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 50515100 of 17610 papers

TitleStatusHype
HumanEval on Latest GPT Models -- 2024Code0
Human in the Loop Adaptive Optimization for Improved Time Series ForecastingCode0
Human-in-the-loop Machine Translation with Large Language ModelCode0
Human-in-the-Loop Synthetic Text Data Inspection with Provenance TrackingCode0
Doc2Dict: Information Extraction as Text GenerationCode0
Adversarial Style Augmentation via Large Language Model for Robust Fake News DetectionCode0
DoCIA: An Online Document-Level Context Incorporation Agent for Speech TranslationCode0
Document Informed Neural Autoregressive Topic Models with Distributional PriorCode0
Document Informed Neural Autoregressive Topic ModelsCode0
Document Modeling with External Attention for Sentence ExtractionCode0
Document Screenshot Retrievers are Vulnerable to Pixel Poisoning AttacksCode0
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERTCode0
Automatic Short Math Answer Grading via In-context Meta-learningCode0
Aligning Language Models to Explicitly Handle AmbiguityCode0
Aligning Language Models Using Follow-up Likelihood as Reward SignalCode0
Does Commonsense help in detecting Sarcasm?Code0
Hyperparameter Power Impact in Transformer Language Model TrainingCode0
ChipSong: A Controllable Lyric Generation System for Chinese Popular SongCode0
Hyperpolyglot LLMs: Cross-Lingual Interpretability in Token EmbeddingsCode0
Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical TextCode0
HypoTermQA: Hypothetical Terms Dataset for Benchmarking Hallucination Tendency of LLMsCode0
Automatic Translation Alignment for Ancient Greek and LatinCode0
Does Transliteration Help Multilingual Language Modeling?Code0
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning MethodsCode0
I-BERT: Inductive Generalization of Transformer to Arbitrary Context LengthsCode0
Choice Fusion as Knowledge for Zero-Shot Dialogue State TrackingCode0
Iceberg: Enhancing HLS Modeling with Synthetic DataCode0
Restricted Recurrent Neural NetworksCode0
Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classificationCode0
ICU: Conquering Language Barriers in Vision-and-Language Modeling by Dividing the Tasks into Image Captioning and Language UnderstandingCode0
Aligning Sentence Simplification with ESL Learner's Proficiency for Language AcquisitionCode0
Do Language Models Exhibit Human-like Structural Priming Effects?Code0
IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and AbductionCode0
Do Language Models Know When They're Hallucinating References?Code0
Do language models plan ahead for future tokens?Code0
Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language ModelCode0
Identifying and Extracting Rare Disease Phenotypes with Large Language ModelsCode0
Automating Code-Related Tasks Through Transformers: The Impact of Pre-trainingCode0
Chunk-aware Alignment and Lexical Constraint for Visual Entailment with Natural Language ExplanationsCode0
Semantic Text Analysis for Detection of Compromised Accounts on Social NetworksCode0
Identifying Conspiracy Theories News based on Event Relation GraphCode0
Do Large Language Models know what humans know?Code0
Chunk-based Nearest Neighbor Machine TranslationCode0
Identifying Human Needs through Social Media: A study on Indian cities during COVID-19Code0
Do Large Language Models Solve ARC Visual Analogies Like People Do?Code0
Do Large Language Model Understand Multi-Intent Spoken Language ?Code0
Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic CuesCode0
Activations and Gradients Compression for Model-Parallel TrainingCode0
Identifying Reasons for Contraceptive Switching from Real-World Data Using Large Language ModelsCode0
IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot ApproachCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified