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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 23512400 of 17610 papers

TitleStatusHype
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression RecognitionCode1
Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific LiteratureCode1
AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizingCode1
LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge RecoveryCode1
DALE: Generative Data Augmentation for Low-Resource Legal NLPCode1
TRAMS: Training-free Memory Selection for Long-range Language ModelingCode1
Vision-Language Pseudo-Labels for Single-Positive Multi-Label LearningCode1
Improving Seq2Seq Grammatical Error Correction via Decoding InterventionsCode1
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed GraphsCode1
Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales DialogueCode1
LLM-in-the-loop: Leveraging Large Language Model for Thematic AnalysisCode1
GeoLM: Empowering Language Models for Geospatially Grounded Language UnderstandingCode1
Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language UnderstandingCode1
Language Model Unalignment: Parametric Red-Teaming to Expose Hidden Harms and BiasesCode1
CXR-LLAVA: a multimodal large language model for interpreting chest X-ray imagesCode1
UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the WebCode1
PromptMix: A Class Boundary Augmentation Method for Large Language Model DistillationCode1
Text generation for dataset augmentation in security classification tasksCode1
Orthogonal Subspace Learning for Language Model Continual LearningCode1
Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst DesignCode1
MARVEL: Unlocking the Multi-Modal Capability of Dense Retrieval via Visual Module PluginCode1
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code SynthesisCode1
MarineGPT: Unlocking Secrets of Ocean to the PublicCode1
MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language ModelCode1
Democratizing Reasoning Ability: Tailored Learning from Large Language ModelCode1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small ModelsCode1
FATA-Trans: Field And Time-Aware Transformer for Sequential Tabular DataCode1
Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative EditingCode1
MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal AdapterCode1
TabuLa: Harnessing Language Models for Tabular Data SynthesisCode1
Knowledge-Augmented Language Model VerificationCode1
Large Language Model for Multi-objective Evolutionary OptimizationCode1
Character-level Chinese Backpack Language ModelsCode1
Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language ModelCode1
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formattingCode1
Watermarking LLMs with Weight QuantizationCode1
EvalCrafter: Benchmarking and Evaluating Large Video Generation ModelsCode1
Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter MergingCode1
SD-HuBERT: Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERTCode1
AutoDIR: Automatic All-in-One Image Restoration with Latent DiffusionCode1
In-context Pretraining: Language Modeling Beyond Document BoundariesCode1
RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language ModelingCode1
Untying the Reversal Curse via Bidirectional Language Model EditingCode1
BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in BiologyCode1
EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic ActivitiesCode1
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language ModelsCode1
Enhancing Conversational Search: Large Language Model-Aided Informative Query RewritingCode1
VLIS: Unimodal Language Models Guide Multimodal Language GenerationCode1
FiLM: Fill-in Language Models for Any-Order GenerationCode1
Large Language Model UnlearningCode1
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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