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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8901–8950 of 17610 papers

TitleStatusHype
Dia-LLaMA: Towards Large Language Model-driven CT Report Generation—0
A Hybrid Approach To Aspect Based Sentiment Analysis Using Transfer Learning—0
Cross-lingual Contextualized Phrase RetrievalCode0
Enhanced Facet Generation with LLM Editing—0
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model—0
Leveraging Large Language Model to Generate a Novel Metaheuristic Algorithm with CRISPE FrameworkCode0
LinkPrompt: Natural and Universal Adversarial Attacks on Prompt-based Language ModelsCode0
AIOS: LLM Agent Operating SystemCode0
RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine ConflictCode0
Learning To Guide Human Decision Makers With Vision-Language Models—0
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models—0
Language Rectified Flow: Advancing Diffusion Language Generation with Probabilistic Flows—0
Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation—0
The Role of n-gram Smoothing in the Age of Neural Networks—0
SPACE-IDEAS: A Dataset for Salient Information Detection in Space InnovationCode0
New Intent Discovery with Attracting and Dispersing Prototype—0
Monotonic Paraphrasing Improves Generalization of Language Model PromptingCode0
Toward Open-Set Human Object Interaction DetectionCode0
Qibo: A Large Language Model for Traditional Chinese Medicine—0
CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral Therapy-based Mental Health Question Answering—0
Heterogeneous Federated Learning with Splited Language Model—0
Protecting Copyrighted Material with Unique Identifiers in Large Language Model TrainingCode0
AI for Biomedicine in the Era of Large Language Models—0
ARO: Large Language Model Supervised Robotics Text2Skill Autonomous Learning—0
Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention—0
Centered Masking for Language-Image Pre-TrainingCode0
SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents—0
Towards a RAG-based Summarization Agent for the Electron-Ion ColliderCode0
Leveraging Large Language Models for Preliminary Security Risk Analysis: A Mission-Critical Case Study—0
Leveraging Zero-Shot Prompting for Efficient Language Model Distillation—0
SceneX: Procedural Controllable Large-scale Scene Generation—0
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classificationCode0
Unifying Large Language Model and Deep Reinforcement Learning for Human-in-Loop Interactive Socially-aware Navigation—0
Measuring Gender and Racial Biases in Large Language Models—0
Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit ReasoningCode0
Text Clustering with Large Language Model Embeddings—0
Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery—0
Language-Based Depth Hints for Monocular Depth Estimation—0
Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case StudyCode0
Make VLM Recognize Visual Hallucination on Cartoon Character Image with Pose Information—0
Controlled Training Data Generation with Diffusion Models—0
An Exploratory Investigation into Code License Infringements in Large Language Model Training DatasetsCode0
Evaluating GPT-4 with Vision on Detection of Radiological Findings on Chest Radiographs—0
CoLLEGe: Concept Embedding Generation for Large Language Models—0
Strategic Responses to Technological Change: Evidence from Online Labor Markets—0
Hear Me, See Me, Understand Me: Audio-Visual Autism Behavior Recognition—0
Bioinformatics and Biomedical Informatics with ChatGPT: Year One Review—0
A Multimodal Approach to Device-Directed Speech Detection with Large Language Models—0
Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering—0
gTBLS: Generating Tables from Text by Conditional Question Answering—0
Show:102550
← PrevPage 179 of 353Next →
All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified