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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 88018850 of 17610 papers

TitleStatusHype
Calibrating the Confidence of Large Language Models by Eliciting Fidelity0
Enhancing Human-Computer Interaction in Chest X-ray Analysis using Vision and Language Model with Eye Gaze Patterns0
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in ConversationCode0
I-Design: Personalized LLM Interior Designer0
Automated User Story Generation with Test Case Specification Using Large Language Model0
Asymptotics of Language Model Alignment0
Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized ContextsCode0
IndoCulture: Exploring Geographically-Influenced Cultural Commonsense Reasoning Across Eleven Indonesian Provinces0
Effective internal language model training and fusion for factorized transducer model0
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language ModelsCode0
Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs0
Sentence-level Media Bias Analysis with Event Relation GraphCode0
Language Model Guided Interpretable Video Action ReasoningCode0
Octopus v2: On-device language model for super agent0
Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments0
M2SA: Multimodal and Multilingual Model for Sentiment Analysis of TweetsCode0
Octopus: On-device language model for function calling of software APIs0
Topic-Based Watermarks for Large Language Models0
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource LanguagesCode0
mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning0
Laying Anchors: Semantically Priming Numerals in Language ModelingCode0
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text GuidanceCode0
Stable Code Technical Report0
The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis0
TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model0
Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training0
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?Code0
Effectively Prompting Small-sized Language Models for Cross-lingual Tasks via Winning Tickets0
AISPACE at SemEval-2024 task 8: A Class-balanced Soft-voting System for Detecting Multi-generator Machine-generated Text0
Do language models plan ahead for future tokens?Code0
Enhancing Reasoning Capacity of SLM using Cognitive Enhancement0
A Controlled Reevaluation of Coreference Resolution ModelsCode0
Humane Speech Synthesis through Zero-Shot Emotion and Disfluency GenerationCode0
CodeBenchGen: Creating Scalable Execution-based Code Generation BenchmarksCode0
Harnessing the Power of Large Language Model for Uncertainty Aware Graph ProcessingCode0
Training-Free Semantic Segmentation via LLM-Supervision0
LLMs are Good Action Recognizers0
Learning to Plan for Language Modeling from Unlabeled DataCode0
Returning to the Start: Generating Narratives with Related EndpointsCode0
WavLLM: Towards Robust and Adaptive Speech Large Language Model0
Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models0
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks WorldCode0
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4Code0
Do Vision-Language Models Understand Compound Nouns?Code0
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code0
Enhancing Content-based Recommendation via Large Language ModelCode0
EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge GraphsCode0
Causal Inference for Human-Language Model CollaborationCode0
Show:102550
← PrevPage 177 of 353Next →

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