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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 12011250 of 17610 papers

TitleStatusHype
Autoregressive Action Sequence Learning for Robotic ManipulationCode2
AntiFold: Improved antibody structure-based design using inverse foldingCode2
ChatterBox: Multi-round Multimodal Referring and GroundingCode2
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual DataCode2
GPT4RoI: Instruction Tuning Large Language Model on Region-of-InterestCode2
GeoChat: Grounded Large Vision-Language Model for Remote SensingCode2
GenSim: A General Social Simulation Platform with Large Language Model based AgentsCode2
LingoQA: Visual Question Answering for Autonomous DrivingCode2
LinVT: Empower Your Image-level Large Language Model to Understand VideosCode2
AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLMCode2
GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual GroundingCode2
Generative Region-Language Pretraining for Open-Ended Object DetectionCode2
Advancing Time Series Classification with Multimodal Language ModelingCode2
GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language ModelCode2
Generative Modeling for Mathematical DiscoveryCode2
Generative Pre-trained Speech Language Model with Efficient Hierarchical TransformerCode2
Citrus: Leveraging Expert Cognitive Pathways in a Medical Language Model for Advanced Medical Decision SupportCode2
Generating Benchmarks for Factuality Evaluation of Language ModelsCode2
Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at ScaleCode2
GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language ModelsCode2
LLark: A Multimodal Instruction-Following Language Model for MusicCode2
LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech EnhancementCode2
Generalized Interpolating Discrete DiffusionCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
Automated Bioinformatics Analysis via AutoBACode2
AutoGRAMS: Autonomous Graphical Agent Modeling SoftwareCode2
Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical TextsCode2
General-purpose, long-context autoregressive modeling with Perceiver ARCode2
CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text LabelsCode2
LLM-A*: Large Language Model Enhanced Incremental Heuristic Search on Path PlanningCode2
GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning AbilitiesCode2
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text ClassificationCode2
AutoFlow: Automated Workflow Generation for Large Language Model AgentsCode2
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language ModelCode2
Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsCode2
GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question AnsweringCode2
Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMsCode2
LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token EmbeddingsCode2
GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructionCode2
From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning TasksCode2
Advancing Language Model Reasoning through Reinforcement Learning and Inference ScalingCode2
Forgetting Transformer: Softmax Attention with a Forget GateCode2
A Training-free LLM-based Approach to General Chinese Character Error CorrectionCode2
A Touch, Vision, and Language Dataset for Multimodal AlignmentCode2
Formal Mathematics Statement Curriculum LearningCode2
From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context ExamplesCode2
A Systematic Study of Cross-Layer KV Sharing for Efficient LLM InferenceCode2
A Systematic Survey of Prompt Engineering on Vision-Language Foundation ModelsCode2
LoQT: Low-Rank Adapters for Quantized PretrainingCode2
FLAME: Financial Large-Language Model Assessment and Metrics EvaluationCode2
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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