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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 35013550 of 17610 papers

TitleStatusHype
Efficient Pre-training of Masked Language Model via Concept-based Curriculum MaskingCode1
Contextual information integration for stance detection via cross-attentionCode1
Efficiently Modeling Long Sequences with Structured State SpacesCode1
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR PredictionCode1
Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on GeneralizationCode1
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language ModelCode1
AutoBencher: Creating Salient, Novel, Difficult Datasets for Language ModelsCode1
Nonparametric Decoding for Generative RetrievalCode1
ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI AgentsCode1
Contextualized Perturbation for Textual Adversarial AttackCode1
Efficient Long Sequence Modeling via State Space Augmented TransformerCode1
RoChBert: Towards Robust BERT Fine-tuning for ChineseCode1
Romanian Speech Recognition Experiments from the ROBIN ProjectCode1
ROSGPT_Vision: Commanding Robots Using Only Language Models' PromptsCode1
Efficient Nearest Neighbor Language ModelsCode1
ELI5: Long Form Question AnsweringCode1
EMScore: Evaluating Video Captioning via Coarse-Grained and Fine-Grained Embedding MatchingCode1
RS-GPT4V: A Unified Multimodal Instruction-Following Dataset for Remote Sensing Image UnderstandingCode1
Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance GenerationCode1
Effective Use of Graph Convolution Network and Contextual Sub-Tree for Commodity News Event ExtractionCode1
Effective Use of Graph Convolution Network and Contextual Sub-Tree forCommodity News Event ExtractionCode1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest ImagesCode1
AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizingCode1
Effective Seed-Guided Topic Discovery by Integrating Multiple Types of ContextsCode1
Effectiveness of self-supervised pre-training for speech recognitionCode1
Effective Sequence-to-Sequence Dialogue State TrackingCode1
Efficient 3D-Aware Facial Image Editing via Attribute-Specific Prompt LearningCode1
Effective Batching for Recurrent Neural Network GrammarsCode1
Effective Attention Sheds Light On InterpretabilityCode1
Effective Human-AI Teams via Learned Natural Language Rules and OnboardingCode1
Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognitionCode1
ECRECer: Enzyme Commission Number Recommendation and Benchmarking based on Multiagent Dual-core LearningCode1
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability DetectionCode1
Sampling from Your Language Model One Byte at a TimeCode1
EDA Corpus: A Large Language Model Dataset for Enhanced Interaction with OpenROADCode1
ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language ModelingCode1
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-trainingCode1
EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote SensingCode1
EasyJudge: an Easy-to-use Tool for Comprehensive Response Evaluation of LLMsCode1
Efficient Content-Based Sparse Attention with Routing TransformersCode1
A Dynamic LLM-Powered Agent Network for Task-Oriented Agent CollaborationCode1
A Neural Algorithm of Artistic StyleCode1
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGsCode1
Dynamic Grained Encoder for Vision TransformersCode1
Controlled Text Generation as Continuous Optimization with Multiple ConstraintsCode1
Dynamic Language Group-Based MoE: Enhancing Code-Switching Speech Recognition with Hierarchical RoutingCode1
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
DuplexMamba: Enhancing Real-time Speech Conversations with Duplex and Streaming CapabilitiesCode1
Dynamic Contextualized Word EmbeddingsCode1
MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal LearningCode1
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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