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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 25512600 of 17610 papers

TitleStatusHype
IterVM: Iterative Vision Modeling Module for Scene Text RecognitionCode1
IvyGPT: InteractiVe Chinese pathwaY language model in medical domainCode1
Language Model Pre-Training with Sparse Latent TypingCode1
JailDAM: Jailbreak Detection with Adaptive Memory for Vision-Language ModelCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
CrAM: A Compression-Aware MinimizerCode1
Detecting Hallucinations in Large Language Model Generation: A Token Probability ApproachCode1
Detecting Language Model Attacks with PerplexityCode1
BreakGPT: A Large Language Model with Multi-stage Structure for Financial Breakout DetectionCode1
Brazilian Portuguese Speech Recognition Using Wav2vec 2.0Code1
Critic-Guided Decoding for Controlled Text GenerationCode1
CPT: Efficient Deep Neural Network Training via Cyclic PrecisionCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM CompressionCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Differential Privacy for Text Analytics via Natural Text SanitizationCode1
A Fully Differentiable Beam Search DecoderCode1
Brain-to-Text Benchmark '24: Lessons LearnedCode1
Dialogue Action Tokens: Steering Language Models in Goal-Directed Dialogue with a Multi-Turn PlannerCode1
Language Models with Image Descriptors are Strong Few-Shot Video-Language LearnersCode1
Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State TrackingCode1
Dialogue State Tracking with a Language Model using Schema-Driven PromptingCode1
DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android BytecodeCode1
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response GenerationCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
Iterative Few-shot Semantic Segmentation from Image Label TextCode1
3D Visual Illusion Depth EstimationCode1
Differential MambaCode1
Jakiro: Boosting Speculative Decoding with Decoupled Multi-Head via MoECode1
Keep CALM and Explore: Language Models for Action Generation in Text-based GamesCode1
BRAINTEASER: Lateral Thinking Puzzles for Large Language ModelsCode1
DiffEditor: Enhancing Speech Editing with Semantic Enrichment and Acoustic ConsistencyCode1
AnthroScore: A Computational Linguistic Measure of AnthropomorphismCode1
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model RecommendationCode1
Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3Code1
Is Child-Directed Speech Effective Training Data for Language Models?Code1
BrainBERT: Self-supervised representation learning for intracranial recordingsCode1
Counterfactual Token Generation in Large Language ModelsCode1
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot LearnersCode1
Can Large Language Model Agents Balance Energy Systems?Code1
The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification TasksCode1
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from TextCode1
A Frustratingly Simple Decoding Method for Neural Text GenerationCode1
CoVR-2: Automatic Data Construction for Composed Video RetrievalCode1
Is BERT Blind? Exploring the Effect of Vision-and-Language Pretraining on Visual Language UnderstandingCode1
Diffuser: Efficient Transformers with Multi-hop Attention Diffusion for Long SequencesCode1
Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language ModelsCode1
Can Large Language Models Write Parallel Code?Code1
IoT-LM: Large Multisensory Language Models for the Internet of ThingsCode1
Cost-effective Instruction Learning for Pathology Vision and Language AnalysisCode1
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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