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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 58515900 of 17610 papers

TitleStatusHype
Grounded Language Agent for Product Search via Intelligent Web InteractionsCode0
Teaching a Multilingual Large Language Model to Understand Multilingual Speech via Multi-Instructional TrainingCode0
Fewer Truncations Improve Language Modeling0
Balancing Speciality and Versatility: a Coarse to Fine Framework for Supervised Fine-tuning Large Language ModelCode0
Generative Text Steganography with Large Language Model0
HLAT: High-quality Large Language Model Pre-trained on AWS TrainiumCode0
Future Language Modeling from Temporal Document HistoryCode0
Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training0
Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering0
Vocabulary-free Image Classification and Semantic SegmentationCode0
From a Lossless (~1.5:1) Compression Algorithm for Llama2 7B Weights to Variable Precision, Variable Range, Compressed Numeric Data Types for CNNs and LLMs0
Exact and Efficient Unlearning for Large Language Model-based Recommendation0
White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs0
Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question AnsweringCode1
Autoregressive Pre-Training on Pixels and TextsCode0
Reasoning on Efficient Knowledge Paths:Knowledge Graph Guides Large Language Model for Domain Question Answering0
Deep Learning and LLM-based Methods Applied to Stellar Lightcurve ClassificationCode3
BayesJudge: Bayesian Kernel Language Modelling with Confidence Uncertainty in Legal Judgment Prediction0
Constructing Benchmarks and Interventions for Combating Hallucinations in LLMsCode1
PRODIS - a speech database and a phoneme-based language model for the study of predictability effects in Polish0
in2IN: Leveraging individual Information to Generate Human INteractionsCode2
ChatShop: Interactive Information Seeking with Language Agents0
Memory Sharing for Large Language Model based AgentsCode1
Unifying Global and Local Scene Entities Modelling for Precise Action SpottingCode0
Knowledge-enhanced Visual-Language Pretraining for Computational PathologyCode1
Language Model Cascades: Token-level uncertainty and beyond0
Negation Triplet Extraction with Syntactic Dependency and Semantic ConsistencyCode0
σ-GPTs: A New Approach to Autoregressive ModelsCode2
Evolving Interpretable Visual Classifiers with Large Language Models0
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction PredictionsCode0
Learn Your Reference Model for Real Good Alignment0
UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmark0
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection0
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language ModelsCode4
Compression Represents Intelligence LinearlyCode2
Unveiling Imitation Learning: Exploring the Impact of Data Falsity to Large Language Model0
Customising General Large Language Models for Specialised Emotion Recognition TasksCode0
JaFIn: Japanese Financial Instruction Dataset0
Compass: Large Multilingual Language Model for South-east Asia0
ToNER: Type-oriented Named Entity Recognition with Generative Language ModelCode0
Test Code Generation for Telecom Software Systems using Two-Stage Generative Model0
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language RepresentationCode0
TEXT2TASTE: A Versatile Egocentric Vision System for Intelligent Reading Assistance Using Large Language Model0
TrafficVLM: A Controllable Visual Language Model for Traffic Video CaptioningCode2
Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts0
Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission0
Self-Selected Attention Span for Accelerating Large Language Model Inference0
DetCLIPv3: Towards Versatile Generative Open-vocabulary Object Detection0
LLMSat: A Large Language Model-Based Goal-Oriented Agent for Autonomous Space ExplorationCode0
Leveraging Large Language Model as Simulated Patients for Clinical Education0
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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