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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 5651–5700 of 17610 papers

TitleStatusHype
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset—0
AfroXLMR-Comet: Multilingual Knowledge Distillation with Attention Matching for Low-Resource languages—0
A Full-duplex Speech Dialogue Scheme Based On Large Language Models—0
A Probability--Quality Trade-off in Aligned Language Models and its Relation to Sampling Adaptors—0
A Fused Large Language Model for Predicting Startup Success—0
AGE: Amharic, Ge’ez and English Parallel Dataset—0
Heterogeneous Federated Learning with Splited Language Model—0
A Generalist Learner for Multifaceted Medical Image Interpretation—0
A Generalized Framework for Hierarchical Word Sequence Language Model—0
Pro-PRIME: A general Temperature-Guided Language model to engineer enhanced Stability and Activity in Proteins—0
A generative framework for conversational laughter: Its 'language model' and laughter sound synthesis—0
A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis—0
A Generative Parser with a Discriminative Recognition Algorithm—0
Agent3D-Zero: An Agent for Zero-shot 3D Understanding—0
AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents—0
Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model—0
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems—0
Agent-Driven Large Language Models for Mandarin Lyric Generation—0
AgentDynEx: Nudging the Mechanics and Dynamics of Multi-Agent Simulations—0
Agentività e telicità in GilBERTo: implicazioni cognitive—0
AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systems—0
AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management—0
AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning—0
AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging—0
Agents for self-driving laboratories applied to quantum computing—0
Agents on the Bench: Large Language Model Based Multi Agent Framework for Trustworthy Digital Justice—0
Agents Play Thousands of 3D Video Games—0
AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials—0
Aggregating Pairwise Semantic Differences for Few-Shot Claim Veracity Classification—0
Aggregating Pairwise Semantic Differences for Few-Shot Claim Veracity Classification—0
Aggression Identification in Social Media: a Transfer Learning Based Approach—0
AG-LSEC: Audio Grounded Lexical Speaker Error Correction—0
A Goal-oriented Neural Conversation Model by Self-Play—0
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks—0
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models—0
A Gradient Analysis Framework for Rewarding Good and Penalizing Bad Examples in Language Models—0
A Graph-Based Approach to String Regeneration—0
Graphmax for Text Generation—0
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction—0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
A Hardware Evaluation Framework for Large Language Model Inference—0
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding—0
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs—0
A Hazard Analysis Framework for Code Synthesis Large Language Models—0
Ahead of the Text: Leveraging Entity Preposition for Financial Relation Extraction—0
A Hetero-functional Graph Resilience Analysis for Convergent Systems-of-Systems—0
A Hierarchical Approach to Neural Context-Aware Modeling—0
A Hierarchical conv-LSTM and LLM Integrated Model for Holistic Stock Forecasting—0
A Hierarchical Entity-Based Approach to Structuralize User Generated Content in Social Media: A Case of Yahoo! Answers—0
A Hierarchical Language Model For Interpretable Graph Reasoning—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified