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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 61016150 of 17610 papers

TitleStatusHype
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text GuidanceCode0
Evalverse: Unified and Accessible Library for Large Language Model EvaluationCode3
Query Performance Prediction using Relevance Judgments Generated by Large Language ModelsCode1
Enhancing Reasoning Capacity of SLM using Cognitive Enhancement0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
Direct Preference Optimization of Video Large Multimodal Models from Language Model RewardCode2
Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model AlignmentCode1
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining0
CodeBenchGen: Creating Scalable Execution-based Code Generation BenchmarksCode0
Harnessing the Power of Large Language Model for Uncertainty Aware Graph ProcessingCode0
A Controlled Reevaluation of Coreference Resolution ModelsCode0
Returning to the Start: Generating Narratives with Related EndpointsCode0
Humane Speech Synthesis through Zero-Shot Emotion and Disfluency GenerationCode0
Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain GeneralizationCode1
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language ModelsCode3
Extensive Self-Contrast Enables Feedback-Free Language Model AlignmentCode1
Training-Free Semantic Segmentation via LLM-Supervision0
WavLLM: Towards Robust and Adaptive Speech Large Language Model0
LLMs are Good Action Recognizers0
DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language ModelCode1
Learning to Plan for Language Modeling from Unlabeled DataCode0
Instruction-Driven Game Engines on Large Language ModelsCode1
NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning0
Controllable and Diverse Data Augmentation with Large Language Model for Low-Resource Open-Domain Dialogue Generation0
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks WorldCode0
Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods0
EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge GraphsCode0
Causal Inference for Human-Language Model CollaborationCode0
Enhancing Content-based Recommendation via Large Language ModelCode0
MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction TasksCode1
Do Vision-Language Models Understand Compound Nouns?Code0
DiLM: Distilling Dataset into Language Model for Text-level Dataset DistillationCode1
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code0
Configurable Safety Tuning of Language Models with Synthetic Preference DataCode1
Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models0
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4Code0
GPTA: Generative Prompt Tuning Assistant for Synergistic Downstream Neural Network Enhancement with LLMs0
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language ModelCode0
Latxa: An Open Language Model and Evaluation Suite for BasqueCode1
ReALM: Reference Resolution As Language Modeling0
PURPLE: Making a Large Language Model a Better SQL Writer0
FSMR: A Feature Swapping Multi-modal Reasoning Approach with Joint Textual and Visual Clues0
Using LLMs to Model the Beliefs and Preferences of Targeted Populations0
The Future of Combating Rumors? Retrieval, Discrimination, and Generation0
VHM: Versatile and Honest Vision Language Model for Remote Sensing Image AnalysisCode2
Large Language Model based Situational Dialogues for Second Language Learning0
MANGO: A Benchmark for Evaluating Mapping and Navigation Abilities of Large Language ModelsCode0
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You WantCode2
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs0
FewUser: Few-Shot Social User Geolocation via Contrastive Learning0
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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