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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 33513400 of 17610 papers

TitleStatusHype
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy RewardCode1
Improved training of end-to-end attention models for speech recognitionCode1
AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross AttentionsCode1
Improving Biomedical Pretrained Language Models with KnowledgeCode1
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced DistillationCode1
LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model DevelopmentCode1
Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-trainingCode1
ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text TranslationCode1
Cross-Thought for Sentence Encoder Pre-trainingCode1
ReZero is All You Need: Fast Convergence at Large DepthCode1
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
Concept Bottleneck Large Language ModelsCode1
Lexically Aware Semi-Supervised Learning for OCR Post-CorrectionCode1
L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient and Accurate Deep LearningCode1
Lifelong Language Knowledge DistillationCode1
Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta InformationCode1
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text DataCode1
Leveraging Label Correlations in a Multi-label Setting: A Case Study in EmotionCode1
Attribution Analysis Meets Model Editing: Advancing Knowledge Correction in Vision Language Models with VisEditCode1
AdaRefiner: Refining Decisions of Language Models with Adaptive FeedbackCode1
Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense RetrievalCode1
Log Parsing: How Far Can ChatGPT Go?Code1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Improving End-to-End SLU performance with Prosodic Attention and DistillationCode1
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot LearningCode1
RoBERTa-wwm-ext Fine-Tuning for Chinese Text ClassificationCode1
Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based TechniquesCode1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small ModelsCode1
Robust Distortion-free Watermarks for Language ModelsCode1
Conditioned Text Generation with Transfer for Closed-Domain Dialogue SystemsCode1
Improving Indonesian Text Classification Using Multilingual Language ModelCode1
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent SpaceCode1
Adaptive Computation Time for Recurrent Neural NetworksCode1
Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language ModelsCode1
ROSGPT_Vision: Commanding Robots Using Only Language Models' PromptsCode1
Cross-lingual Visual Pre-training for Multimodal Machine TranslationCode1
Let the Models Respond: Interpreting Language Model Detoxification Through the Lens of Prompt DependenceCode1
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech RecognitionCode1
Less is More: Task-aware Layer-wise Distillation for Language Model CompressionCode1
Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation ApproachCode1
Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!Code1
Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP StandardsCode1
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word AlignmentCode1
Configurable Safety Tuning of Language Models with Synthetic Preference DataCode1
Leveraging Natural Supervision for Language Representation Learning and GenerationCode1
LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online ContentCode1
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text GenerationCode1
ConfliBERT: A Language Model for Political ConflictCode1
A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human LevelCode1
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak DecoderCode1
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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