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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 61016150 of 17610 papers

TitleStatusHype
Sketch-Guided Constrained Decoding for Boosting Blackbox Large Language Models without Logit AccessCode0
TRAM: Bridging Trust Regions and Sharpness Aware MinimizationCode0
Overcoming Barriers to Skill Injection in Language Modeling: Case Study in ArithmeticCode0
LLMs as Educational Analysts: Transforming Multimodal Data Traces into Actionable Reading Assessment ReportsCode0
Skim-Attention: Learning to Focus via Document LayoutCode0
Two-Stage Classifier for COVID-19 Misinformation Detection Using BERT: a Study on Indonesian TweetsCode0
Memory and Knowledge Augmented Language Models for Inferring Salience in Long-Form StoriesCode0
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot LearningCode0
Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional AnaloguesCode0
Overcoming Vision Language Model Challenges in Diagram Understanding: A Proof-of-Concept with XML-Driven Large Language Models SolutionsCode0
Prompt-enhanced Network for Hateful Meme ClassificationCode0
Optimizing Deep Neural Networks using Safety-Guided Self CompressionCode0
Keep It Private: Unsupervised Privatization of Online TextCode0
Optimization of Armv9 architecture general large language model inference performance based on Llama.cppCode0
SHINE: Saliency-aware HIerarchical NEgative Ranking for Compositional Temporal GroundingCode0
Shifting Mean Activation Towards Zero with Bipolar Activation FunctionsCode0
Shifting from endangerment to rebirth in the Artificial Intelligence Age: An Ensemble Machine Learning Approach for Hawrami Text ClassificationCode0
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only PassesCode0
Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple DomainsCode0
ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank AdaptationCode0
Learning Deterministic Weighted Automata with Queries and CounterexamplesCode0
Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text NormalizationCode0
Larger Probes Tell a Different Story: Extending Psycholinguistic Datasets Via In-Context LearningCode0
MetaCoCo: A New Few-Shot Classification Benchmark with Spurious CorrelationCode0
Meta-Context Transformers for Domain-Specific Response GenerationCode0
Large Scale Language Modeling: Converging on 40GB of Text in Four HoursCode0
SLIDE: Integrating Speech Language Model with LLM for Spontaneous Spoken Dialogue GenerationCode0
Learning to Maximize Mutual Information for Chain-of-Thought DistillationCode0
Shaking Up VLMs: Comparing Transformers and Structured State Space Models for Vision & Language ModelingCode0
Labels Generated by Large Language Model Helps Measuring People's Empathy in VitroCode0
SG-Net: Syntax-Guided Machine Reading ComprehensionCode0
PACuna: Automated Fine-Tuning of Language Models for Particle AcceleratorsCode0
Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement LearningCode0
PADA: Pruning Assisted Domain Adaptation for Self-Supervised Speech RepresentationsCode0
Transcending the Attention Paradigm: Representation Learning from Geospatial Social Media DataCode0
The World of an Octopus: How Reporting Bias Influences a Language Model's Perception of ColorCode0
SLM-Mod: Small Language Models Surpass LLMs at Content ModerationCode0
The World of an Octopus: How Reporting Bias Influences a Language Model’s Perception of ColorCode0
Language Models as Knowledge Bases?Code0
Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive LearningCode0
Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language InferenceCode0
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information NetworksCode0
WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical CaseCode0
Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language ModelCode0
Seventeenth-Century Spanish American Notary Records for Fine-Tuning Spanish Large Language ModelsCode0
Meta Fine-Tuning Neural Language Models for Multi-Domain Text MiningCode0
The Z-loss: a shift and scale invariant classification loss belonging to the Spherical FamilyCode0
OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question AnsweringCode0
LLMSat: A Large Language Model-Based Goal-Oriented Agent for Autonomous Space ExplorationCode0
Thieves on Sesame Street! Model Extraction of BERT-based APIsCode0
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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