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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 34013450 of 17610 papers

TitleStatusHype
Morphological evaluation of subwords vocabulary used by BETO language model0
Neutral residues: revisiting adapters for model extension0
Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent ExplorationCode4
Learning the Latent Rules of a Game from Data: A Chess Story0
FAN: Fourier Analysis NetworksCode3
NL-Eye: Abductive NLI for Images0
Leveraging Large Language Models to Enhance Personalized Recommendations in E-commerce0
Long-range gene expression prediction with token alignment of large language model0
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model CompressionCode1
A Two-Stage Proactive Dialogue Generator for Efficient Clinical Information Collection Using Large Language Model0
EMMA: Efficient Visual Alignment in Multi-Modal LLMsCode1
Enhancing Screen Time Identification in Children with a Multi-View Vision Language Model and Screen Time Tracker0
LLM-Augmented Symbolic Reinforcement Learning with Landmark-Based Task Decomposition0
Generate then Refine: Data Augmentation for Zero-shot Intent DetectionCode0
Racing Thoughts: Explaining Contextualization Errors in Large Language Models0
FARM: Functional Group-Aware Representations for Small Molecules0
LS-HAR: Language Supervised Human Action Recognition with Salient Fusion, Construction Sites as a Use-Case0
OCC-MLLM-Alpha:Empowering Multi-modal Large Language Model for the Understanding of Occluded Objects with Self-Supervised Test-Time Learning0
TypedThinker: Typed Thinking Improves Large Language Model ReasoningCode0
SciPrompt: Knowledge-augmented Prompting for Fine-grained Categorization of Scientific TopicsCode0
Automatic deductive coding in discourse analysis: an application of large language models in learning analyticsCode0
Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads on Consumer-Grade DevicesCode1
Frozen Large Language Models Can Perceive Paralinguistic Aspects of Speech0
Knowledge Entropy Decay during Language Model Pretraining Hinders New Knowledge AcquisitionCode1
Leopard: A Vision Language Model For Text-Rich Multi-Image TasksCode2
ConServe: Harvesting GPUs for Low-Latency and High-Throughput Large Language Model Serving0
Unveiling Language Skills via Path-Level Circuit DiscoveryCode0
Elaborative Subtopic Query Reformulation for Broad and Indirect Queries in Travel Destination RecommendationCode0
Mind Scramble: Unveiling Large Language Model Psychology Via TypoglycemiaCode0
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence ModelingCode1
Spoken Grammar Assessment Using LLM0
Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models0
From Reward Shaping to Q-Shaping: Achieving Unbiased Learning with LLM-Guided Knowledge0
When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o10
OCC-MLLM:Empowering Multimodal Large Language Model For the Understanding of Occluded Objects0
Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling0
Agent-Driven Large Language Models for Mandarin Lyric Generation0
Integrating Protein Sequence and Expression Level to Analysis Molecular Characterization of Breast Cancer Subtypes0
Investigating on RLHF methodology0
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective0
End-to-End Speech Recognition with Pre-trained Masked Language Model0
ERASMO: Leveraging Large Language Models for Enhanced Clustering SegmentationCode0
Language Enhanced Model for Eye (LEME): An Open-Source Ophthalmology-Specific Large Language Model0
Khattat: Enhancing Readability and Concept Representation of Semantic Typography0
PclGPT: A Large Language Model for Patronizing and Condescending Language DetectionCode0
Optimizing Token Usage on Large Language Model Conversations Using the Design Structure Matrix0
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis0
Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model PromptingCode0
Removing Distributional Discrepancies in Captions Improves Image-Text Alignment0
ReXplain: Translating Radiology into Patient-Friendly Video Reports0
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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