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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 99019950 of 17610 papers

TitleStatusHype
Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM's Translation Capability0
Large-Scale Text Analysis Using Generative Language Models: A Case Study in Discovering Public Value Expressions in AI Patents0
Token-wise Decomposition of Autoregressive Language Model Hidden States for Analyzing Model PredictionsCode0
Controllable Speaking Styles Using a Large Language Model0
Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackCode2
DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation LearningCode1
AD-KD: Attribution-Driven Knowledge Distillation for Language Model CompressionCode1
A Better Way to Do Masked Language Model ScoringCode1
A Survey on Zero Pronoun Translation0
CageViT: Convolutional Activation Guided Efficient Vision Transformer0
PaLM 2 Technical Report0
PMC-VQA: Visual Instruction Tuning for Medical Visual Question AnsweringCode1
SLiC-HF: Sequence Likelihood Calibration with Human Feedback0
Generation of 3D Molecules in Pockets via Language Model0
SatLM: Satisfiability-Aided Language Models Using Declarative PromptingCode1
Application-Agnostic Language Modeling for On-Device ASR0
SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and VerificationCode3
MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with TransformersCode1
StructGPT: A General Framework for Large Language Model to Reason over Structured DataCode2
Pre-Training to Learn in ContextCode1
Towards Unifying Multi-Lingual and Cross-Lingual Summarization0
CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic ModelingCode0
Dual-Alignment Pre-training for Cross-lingual Sentence EmbeddingCode1
NeuSTIP: A Novel Neuro-Symbolic Model for Link and Time Prediction in Temporal Knowledge Graphs0
Large Language Model Guided Tree-of-ThoughtCode2
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference ChecklistCode3
Natural Language Decomposition and Interpretation of Complex Utterances0
Estimating the Causal Effects of Natural Logic Features in Neural NLI Models0
A Language Model of Java Methods with Train/Test DeduplicationCode0
DarkBERT: A Language Model for the Dark Side of the Internet0
Exploring In-Context Learning Capabilities of Foundation Models for Generating Knowledge Graphs from Text0
Knowledge Rumination for Pre-trained Language ModelsCode1
Unsupervised Sentence Representation Learning with Frequency-induced Adversarial Tuning and Incomplete Sentence FilteringCode0
Watermarking Text Generated by Black-Box Language ModelsCode1
Improving End-to-End SLU performance with Prosodic Attention and DistillationCode1
Mobile-Env: Building Qualified Evaluation Benchmarks for LLM-GUI InteractionCode1
Scalable Educational Question Generation with Pre-trained Language ModelsCode0
Pre-trained Language Model with Prompts for Temporal Knowledge Graph CompletionCode1
The Machine Psychology of Cooperation: Can GPT models operationalise prompts for altruism, cooperation, competitiveness and selfishness in economic games?Code1
Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts0
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers0
Learning to Reason over Scene Graphs: A Case Study of Finetuning GPT-2 into a Robot Language Model for Grounded Task Planning0
Using Language Models to Detect Alarming Student Responses0
Two-in-One: A Model Hijacking Attack Against Text Generation Models0
Prompt Learning to Mitigate Catastrophic Forgetting in Cross-lingual Transfer for Open-domain Dialogue GenerationCode0
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model RecommendationCode1
LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model DevelopmentCode1
Text2Cohort: Facilitating Intuitive Access to Biomedical Data with Natural Language Cohort DiscoveryCode0
ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced AdapterCode1
Self-Chained Image-Language Model for Video Localization and Question AnsweringCode1
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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