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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 651700 of 17610 papers

TitleStatusHype
Language Modeling by Language ModelsCode2
Adapting Language Models to Compress ContextsCode2
Language Model CascadesCode2
Language Model Crossover: Variation through Few-Shot PromptingCode2
Language Models Can Improve Event Prediction by Few-Shot Abductive ReasoningCode2
KV Shifting Attention Enhances Language ModelingCode2
LaMI-DETR: Open-Vocabulary Detection with Language Model InstructionCode2
CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text LabelsCode2
KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model ApplicationCode2
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale InstructionsCode2
Adapting a Language Model While Preserving its General KnowledgeCode2
ClipCap: CLIP Prefix for Image CaptioningCode2
Knowledge Representation Learning: A Quantitative ReviewCode2
Knowledge Circuits in Pretrained TransformersCode2
Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMsCode2
LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity EnhancementCode2
Language Models can Solve Computer TasksCode2
ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language modelCode2
A Touch, Vision, and Language Dataset for Multimodal AlignmentCode2
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language ModelCode2
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document UnderstandingCode2
VLKEB: A Large Vision-Language Model Knowledge Editing BenchmarkCode2
KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World KnowledgeCode2
AdapterFusion: Non-Destructive Task Composition for Transfer LearningCode2
ABodyBuilder3: Improved and scalable antibody structure predictionsCode2
Just read twice: closing the recall gap for recurrent language modelsCode2
A Training-free LLM-based Approach to General Chinese Character Error CorrectionCode2
Kani: A Lightweight and Highly Hackable Framework for Building Language Model ApplicationsCode2
KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph CompletionCode2
Citrus: Leveraging Expert Cognitive Pathways in a Medical Language Model for Advanced Medical Decision SupportCode2
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPOCode2
Iteration of Thought: Leveraging Inner Dialogue for Autonomous Large Language Model ReasoningCode2
Introducing Visual Perception Token into Multimodal Large Language ModelCode2
500xCompressor: Generalized Prompt Compression for Large Language ModelsCode2
Large Language Model Instruction Following: A Survey of Progresses and ChallengesCode2
Jailbreaking Attack against Multimodal Large Language ModelCode2
A Systematic Study of Cross-Layer KV Sharing for Efficient LLM InferenceCode2
A Systematic Survey of Prompt Engineering on Vision-Language Foundation ModelsCode2
CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language ModelCode2
Jailbreak Vision Language Models via Bi-Modal Adversarial PromptCode2
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information ExtractionCode2
Language Representations Can be What Recommenders Need: Findings and PotentialsCode2
Memorizing TransformersCode2
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model AgentsCode2
Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language ModelCode2
AdaFisher: Adaptive Second Order Optimization via Fisher InformationCode2
Asynchronous Large Language Model Enhanced Planner for Autonomous DrivingCode2
Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion TokensCode2
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision GeneralistsCode2
In-Context Language Learning: Architectures and AlgorithmsCode2
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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