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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 39514000 of 17610 papers

TitleStatusHype
DeeperImpact: Optimizing Sparse Learned Index StructuresCode1
Deep Indexed Active Learning for Matching Heterogeneous Entity RepresentationsCode1
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt CollectionsCode1
MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and CollaborationCode1
DARTS: Differentiable Architecture SearchCode1
Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language ModelCode1
Machine learning as a model for cultural learning: Teaching an algorithm what it means to be fatCode1
Walert: Putting Conversational Search Knowledge into Action by Building and Evaluating a Large Language Model-Powered ChatbotCode1
MG-MotionLLM: A Unified Framework for Motion Comprehension and Generation across Multiple GranularitiesCode1
BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic ParsingCode1
MAGMA -- Multimodal Augmentation of Generative Models through Adapter-based FinetuningCode1
Meta-learning via Language Model In-context TuningCode1
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order OptimizationCode1
Making Language Models Better Tool Learners with Execution FeedbackCode1
Beheshti-NER: Persian Named Entity Recognition Using BERTCode1
Advancing Beyond Identification: Multi-bit Watermark for Large Language ModelsCode1
Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLPCode1
Deep contextualized word representationsCode1
MetaICL: Learning to Learn In ContextCode1
Decoupled Visual Interpretation and Linguistic Reasoning for Math Problem SolvingCode1
MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction TasksCode1
BECEL: Benchmark for Consistency Evaluation of Language ModelsCode1
An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model TokenizersCode1
Decouple knowledge from parameters for plug-and-play language modelingCode1
Unifying Segment Anything in Microscopy with Multimodal Large Language ModelCode1
Mapping Memes to Words for Multimodal Hateful Meme ClassificationCode1
Mark My Words: Analyzing and Evaluating Language Model WatermarksCode1
MarineGPT: Unlocking Secrets of Ocean to the PublicCode1
MetaLA: Unified Optimal Linear Approximation to Softmax Attention MapCode1
BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language ModelsCode1
A Cheaper and Better Diffusion Language Model with Soft-Masked NoiseCode1
Decoding-Time Language Model Alignment with Multiple ObjectivesCode1
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability DetectionCode1
Meta-Learning Online Adaptation of Language ModelsCode1
Meta-Prompting for Automating Zero-shot Visual Recognition with LLMsCode1
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP ModelsCode1
MERMAID: Metaphor Generation with Symbolism and Discriminative DecodingCode1
An Efficient Self-Supervised Cross-View Training For Sentence EmbeddingCode1
End-to-End Beam Retrieval for Multi-Hop Question AnsweringCode1
An Efficient Multilingual Language Model Compression through Vocabulary TrimmingCode1
Merging Text Transformer Models from Different InitializationsCode1
Deciphering antibody affinity maturation with language models and weakly supervised learningCode1
Decision Transformer: Reinforcement Learning via Sequence ModelingCode1
Debiasing the Cloze Task in Sequential Recommendation with Bidirectional TransformersCode1
DebUnc: Improving Large Language Model Agent Communication With Uncertainty MetricsCode1
Matching Patients to Clinical Trials with Large Language ModelsCode1
Balanced Data Sampling for Language Model Training with ClusteringCode1
What's the Magic Word? A Control Theory of LLM PromptingCode1
Declaration-based Prompt Tuning for Visual Question AnsweringCode1
Merging Feed-Forward Sublayers for Compressed TransformersCode1
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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