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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 16511700 of 17610 papers

TitleStatusHype
DiffEditor: Enhancing Speech Editing with Semantic Enrichment and Acoustic ConsistencyCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
LOLA -- An Open-Source Massively Multilingual Large Language ModelCode1
Improving Spoken Language Modeling with Phoneme Classification: A Simple Fine-tuning ApproachCode1
Enhancing RL Safety with Counterfactual LLM ReasoningCode1
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic PuzzlesCode1
Symbolic Regression with a Learned Concept LibraryCode1
DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and ClassificationCode1
ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction TuningCode1
Explaining Datasets in Words: Statistical Models with Natural Language ParametersCode1
AudioBERT: Audio Knowledge Augmented Language ModelCode1
WirelessAgent: Large Language Model Agents for Intelligent Wireless NetworksCode1
Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language ModelCode1
Salmon: A Suite for Acoustic Language Model EvaluationCode1
AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric KnowledgeCode1
PiTe: Pixel-Temporal Alignment for Large Video-Language ModelCode1
STLM Engineering Report: DropoutCode1
Retrofitting Temporal Graph Neural Networks with TransformerCode1
AbGPT: De Novo Antibody Design via Generative Language ModelingCode1
TextToucher: Fine-Grained Text-to-Touch GenerationCode1
Sparse Rewards Can Self-Train Dialogue AgentsCode1
AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language ModelCode1
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced DistillationCode1
RouterRetriever: Routing over a Mixture of Expert Embedding ModelsCode1
FuzzCoder: Byte-level Fuzzing Test via Large Language ModelCode1
Towards Real-World Adverse Weather Image Restoration: Enhancing Clearness and Semantics with Vision-Language ModelsCode1
The Compressor-Retriever Architecture for Language Model OSCode1
Co-Learning: Code Learning for Multi-Agent Reinforcement Collaborative Framework with Conversational Natural Language InterfacesCode1
Recoverable Compression: A Multimodal Vision Token Recovery Mechanism Guided by Text InformationCode1
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language ModelCode1
MultiMath: Bridging Visual and Mathematical Reasoning for Large Language ModelsCode1
Legilimens: Practical and Unified Content Moderation for Large Language Model ServicesCode1
RSTeller: Scaling Up Visual Language Modeling in Remote Sensing with Rich Linguistic Semantics from Openly Available Data and Large Language ModelsCode1
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelCode1
SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space ModelsCode1
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language ModelsCode1
AgentMove: Predicting Human Mobility Anywhere Using Large Language Model based Agentic FrameworkCode1
Grounded Multi-Hop VideoQA in Long-Form Egocentric VideosCode1
IAA: Inner-Adaptor Architecture Empowers Frozen Large Language Model with Multimodal CapabilitiesCode1
VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation ModelsCode1
SLM Meets LLM: Balancing Latency, Interpretability and Consistency in Hallucination DetectionCode1
CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical ResearcherCode1
FocusLLM: Precise Understanding of Long Context by Dynamic CondensingCode1
Approaching Deep Learning through the Spectral Dynamics of WeightsCode1
ProteinGPT: Multimodal LLM for Protein Property Prediction and Structure UnderstandingCode1
Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP StandardsCode1
MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt TuningCode1
UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and GenerationCode1
Great Memory, Shallow Reasoning: Limits of kNN-LMsCode1
HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language ModelsCode1
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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