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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 651–700 of 17610 papers

TitleStatusHype
MilChat: Introducing Chain of Thought Reasoning and GRPO to a Multimodal Small Language Model for Remote Sensing—0
Reassessing Large Language Model Boolean Query Generation for Systematic Reviews—0
SLAG: Scalable Language-Augmented Gaussian Splatting—0
Putting It All into Context: Simplifying Agents with LCLMs—0
Bridging Large Language Models and Single-Cell Transcriptomics in Dissecting Selective Motor Neuron Vulnerability—0
Domain Regeneration: How well do LLMs match syntactic properties of text domains?—0
Kalman Filter Enhanced GRPO for Reinforcement Learning-Based Language Model ReasoningCode1
Semantic Retention and Extreme Compression in LLMs: Can We Have Both?—0
Relative Overfitting and Accept-Reject Framework—0
Comet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity—0
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to PosttrainingCode5
On the Robustness of Reward Models for Language Model AlignmentCode0
DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented GenerationCode2
Matrix Is All You Need—0
Impact of SMILES Notational Inconsistencies on Chemical Language Model PerformanceCode0
TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking—0
Web Page Classification using LLMs for Crawling SupportCode0
NewsNet-SDF: Stochastic Discount Factor Estimation with Pretrained Language Model News Embeddings via Adversarial Networks—0
GuidedQuant: Large Language Model Quantization via Exploiting End Loss GuidanceCode2
Convert Language Model into a Value-based Strategic Planner—0
Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations—0
Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models—0
The Sound of Populism: Distinct Linguistic Features Across Populist Variants—0
Recovering Event Probabilities from Large Language Model Embeddings via Axiomatic Constraints—0
Enfoque Odychess: Un método dialéctico, constructivista y adaptativo para la enseñanza del ajedrez con inteligencias artificiales generativas—0
Is your multimodal large language model a good science tutor?—0
Natural Reflection Backdoor Attack on Vision Language Model for Autonomous Driving—0
Quantum State Preparation via Large-Language-Model-Driven Evolution—0
An empathic GPT-based chatbot to talk about mental disorders with Spanish teenagers—0
Summarisation of German Judgments in conjunction with a Class-based EvaluationCode0
Tell Me Who Your Students Are: GPT Can Generate Valid Multiple-Choice Questions When Students' (Mis)Understanding Is Hinted—0
Camera Control at the Edge with Language Models for Scene Understanding—0
Free and Fair Hardware: A Pathway to Copyright Infringement-Free Verilog Generation using LLMs—0
Elastic Weight Consolidation for Full-Parameter Continual Pre-Training of Gemma2—0
MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from TextbooksCode1
A Large Language Model-Enhanced Q-learning for Capacitated Vehicle Routing Problem with Time Windows—0
Understanding Stragglers in Large Model Training Using What-if AnalysisCode0
CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis—0
Large Language Model-driven Security Assistant for Internet of Things via Chain-of-Thought—0
Scalable LLM Math Reasoning Acceleration with Low-rank Distillation—0
Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability DetectionCode0
Privacy-Preserving Transformers: SwiftKey's Differential Privacy Implementation—0
Stealthy LLM-Driven Data Poisoning Attacks Against Embedding-Based Retrieval-Augmented Recommender Systems—0
PADriver: Towards Personalized Autonomous Driving—0
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant—0
Image-Text Relation Prediction for Multilingual Tweets—0
Q-Heart: ECG Question Answering via Knowledge-Informed Multimodal LLMs—0
Lossless Compression of Large Language Model-Generated Text via Next-Token Prediction—0
Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codes—0
Bringing legal knowledge to the public by constructing a legal question bank using large-scale pre-trained language model—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