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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 12511300 of 17610 papers

TitleStatusHype
GenSim: A General Social Simulation Platform with Large Language Model based AgentsCode2
GeoChat: Grounded Large Vision-Language Model for Remote SensingCode2
Discovering Latent Knowledge in Language Models Without SupervisionCode2
GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language ModelsCode2
Generative Pre-trained Speech Language Model with Efficient Hierarchical TransformerCode2
MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based AgentsCode2
Discrete Diffusion Modeling by Estimating the Ratios of the Data DistributionCode2
Memorizing TransformersCode2
Generative Modeling for Mathematical DiscoveryCode2
Metadata Conditioning Accelerates Language Model Pre-trainingCode2
BEYOND DIALOGUE: A Profile-Dialogue Alignment Framework Towards General Role-Playing Language ModelCode2
MetaOpenFOAM 2.0: Large Language Model Driven Chain of Thought for Automating CFD Simulation and Post-ProcessingCode2
Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at ScaleCode2
Generating Benchmarks for Factuality Evaluation of Language ModelsCode2
Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsCode2
Generative Region-Language Pretraining for Open-Ended Object DetectionCode2
Agent-R: Training Language Model Agents to Reflect via Iterative Self-TrainingCode2
Generalized Interpolating Discrete DiffusionCode2
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language ModelCode2
BianCang: A Traditional Chinese Medicine Large Language ModelCode2
GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning AbilitiesCode2
MiniPLM: Knowledge Distillation for Pre-Training Language ModelsCode2
General-purpose, long-context autoregressive modeling with Perceiver ARCode2
From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning TasksCode2
Mixture of A Million ExpertsCode2
Mixture of Tokens: Continuous MoE through Cross-Example AggregationCode2
AgentSims: An Open-Source Sandbox for Large Language Model EvaluationCode2
MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models AgentsCode2
ARAGOG: Advanced RAG Output GradingCode2
Controlling Vision-Language Models for Multi-Task Image RestorationCode2
From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context ExamplesCode2
Forgetting Transformer: Softmax Attention with a Forget GateCode2
Language Model Powered Digital Biology with BRADCode2
Formal Mathematics Statement Curriculum LearningCode2
Block-Recurrent TransformersCode2
Controlled Text Generation via Language Model ArithmeticCode2
An Egocentric Vision-Language Model based Portable Real-time Smart AssistantCode2
Montessori-Instruct: Generate Influential Training Data Tailored for Student LearningCode2
DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading SystemsCode2
Full-Duplex-Bench: A Benchmark to Evaluate Full-duplex Spoken Dialogue Models on Turn-taking CapabilitiesCode2
FLAIR: VLM with Fine-grained Language-informed Image RepresentationsCode2
Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language ModelsCode2
biorecap: an R package for summarizing bioRxiv preprints with a local LLMCode2
Motion-Agent: A Conversational Framework for Human Motion Generation with LLMsCode2
FLAME: Financial Large-Language Model Assessment and Metrics EvaluationCode2
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character DesignCode2
MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information RetrievalCode2
FIRST: Faster Improved Listwise Reranking with Single Token DecodingCode2
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsCode2
G1: Bootstrapping Perception and Reasoning Abilities of Vision-Language Model via Reinforcement LearningCode2
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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