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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 60016050 of 17610 papers

TitleStatusHype
X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model0
How Many Languages Make Good Multilingual Instruction Tuning? A Case Study on BLOOM0
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?Code1
SqueezeAttention: 2D Management of KV-Cache in LLM Inference via Layer-wise Optimal BudgetCode1
SilverSight: A Multi-Task Chinese Financial Large Language Model Based on Adaptive Semantic Space Learning0
Hidden You Malicious Goal Into Benign Narratives: Jailbreak Large Language Models through Logic Chain Injection0
Towards Understanding the Influence of Reward Margin on Preference Model Performance0
How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse0
GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling0
Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm0
What Happens When Small Is Made Smaller? Exploring the Impact of Compression on Small Data Pretrained Language Models0
Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology0
Binary Classifier Optimization for Large Language Model Alignment0
Physics Event Classification Using Large Language ModelsCode0
Implicit Bias of AdamW: _ Norm Constrained Optimization0
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving0
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model0
Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to LuxembourgishCode0
Image-Text Co-Decomposition for Text-Supervised Semantic SegmentationCode1
player2vec: A Language Modeling Approach to Understand Player Behavior in Games0
BuDDIE: A Business Document Dataset for Multi-task Information Extraction0
Dwell in the Beginning: How Language Models Embed Long Documents for Dense RetrievalCode0
A Comparison of Methods for Evaluating Generative IRCode0
BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language ModelsCode1
Mitigating LLM Hallucinations via Conformal Abstention0
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringCode1
CONFLARE: CONFormal LArge language model REtrievalCode1
Bias Amplification in Language Model Evolution: An Iterated Learning PerspectiveCode0
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open ChallengesCode0
Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation RegularizationCode0
AutoWebGLM: A Large Language Model-based Web Navigating AgentCode4
OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning0
Multi-modal Learning for WebAssembly Reverse Engineering0
Standardizing Knowledge Engineering Practices with a Reference Architecture0
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis0
nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thought on Emotion StatesCode1
Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought0
Edisum: Summarizing and Explaining Wikipedia Edits at ScaleCode0
SemGrasp: Semantic Grasp Generation via Language Aligned Discretization0
Diverse and Tailored Image Generation for Zero-shot Multi-label Classification0
Towards Pareto Optimal Throughput in Small Language Model Serving0
DeViDe: Faceted medical knowledge for improved medical vision-language pre-training0
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual TokensCode4
Sailor: Open Language Models for South-East AsiaCode4
Attributions toward Artificial Agents in a modified Moral Turing Test0
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech0
From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives0
Improving Topic Relevance Model by Mix-structured Summarization and LLM-based Data Augmentation0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison0
AWOL: Analysis WithOut synthesis using Language0
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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