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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 28012850 of 17610 papers

TitleStatusHype
Exploring the Landscape for Generative Sequence Models for Specialized Data SynthesisCode0
Training Compute-Optimal Protein Language ModelsCode1
Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language ModelsCode1
RAGViz: Diagnose and Visualize Retrieval-Augmented GenerationCode2
Context Parallelism for Scalable Million-Token Inference0
High-performance automated abstract screening with large language model ensembles0
A Deep Dive Into Large Language Model Code Generation Mistakes: What and Why?0
GraphXForm: Graph transformer for computer-aided molecular designCode1
Enriching Tabular Data with Contextual LLM Embeddings: A Comprehensive Ablation Study for Ensemble Classifiers0
Large Language Model Supply Chain: Open Problems From the Security Perspective0
Can Multimodal Large Language Model Think Analogically?0
Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks0
A Mechanistic Explanatory Strategy for XAI0
Rule Based Rewards for Language Model SafetyCode3
PRIMO: Progressive Induction for Multi-hop Open Rule Generation0
Can Large Language Model Predict Employee Attrition?0
Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agent0
Interacting Large Language Model Agents. Interpretable Models and Social Learning0
Adding Error Bars to Evals: A Statistical Approach to Language Model Evaluations0
Enhancing AAC Software for Dysarthric Speakers in e-Health Settings: An Evaluation Using TORGO0
Leveraging Large Language Models for Code-Mixed Data Augmentation in Sentiment AnalysisCode0
Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model0
Multi-expert Prompting Improves Reliability, Safety, and Usefulness of Large Language ModelsCode1
Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in TransformersCode0
LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering0
Enhancing the Traditional Chinese Medicine Capabilities of Large Language Model through Reinforcement Learning from AI Feedback0
RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models0
Unified Generative and Discriminative Training for Multi-modal Large Language Models0
SPRING Lab IITM's submission to Low Resource Indic Language Translation Shared Task0
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents0
Lingma SWE-GPT: An Open Development-Process-Centric Language Model for Automated Software ImprovementCode3
Randomized Autoregressive Visual GenerationCode5
DEREC-SIMPRO: unlock Language Model benefits to advance Synthesis in Data Clean Room0
LLaMo: Large Language Model-based Molecular Graph AssistantCode1
MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees0
Schema Augmentation for Zero-Shot Domain Adaptation in Dialogue State Tracking0
Beyond Label Attention: Transparency in Language Models for Automated Medical Coding via Dictionary Learning0
Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility PredictionCode1
Stereo-Talker: Audio-driven 3D Human Synthesis with Prior-Guided Mixture-of-Experts0
EchoNarrator: Generating natural text explanations for ejection fraction predictionsCode0
Thought Space Explorer: Navigating and Expanding Thought Space for Large Language Model Reasoning0
π_0: A Vision-Language-Action Flow Model for General Robot Control0
Matchmaker: Self-Improving Large Language Model Programs for Schema Matching0
Interpretable Language Modeling via Induction-head Ngram ModelsCode1
What is Wrong with Perplexity for Long-context Language Modeling?Code2
GPT or BERT: why not both?Code2
Web-Scale Visual Entity Recognition: An LLM-Driven Data Approach0
Morphological Typology in BPE Subword Productivity and Language Modeling0
Weight decay induces low-rank attention layers0
Towards Reliable Alignment: Uncertainty-aware RLHF0
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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