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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 2401–2450 of 17610 papers

TitleStatusHype
Text-to-3D Gaussian Splatting with Physics-Grounded Motion Generation—0
DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNACode1
Enhancing LLMs for Impression Generation in Radiology Reports through a Multi-Agent System—0
C^2LEVA: Toward Comprehensive and Contamination-Free Language Model EvaluationCode2
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora—0
CigTime: Corrective Instruction Generation Through Inverse Motion Editing—0
From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go—0
PETapter: Leveraging PET-style classification heads for modular few-shot parameter-efficient fine-tuning—0
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling—0
Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report GenerationCode0
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning—0
QueEn: A Large Language Model for Quechua-English Translation—0
Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training—0
Transformers Can Navigate Mazes With Multi-Step PredictionCode1
Smoothie: Label Free Language Model RoutingCode1
A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challenges—0
Generative Humanization for Therapeutic Antibodies—0
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation—0
LinVT: Empower Your Image-level Large Language Model to Understand VideosCode2
Espresso: High Compression For Rich Extraction From Videos for Your Vision-Language Model—0
A Practical Examination of AI-Generated Text Detectors for Large Language Models—0
Flash Communication: Reducing Tensor Parallelization Bottleneck for Fast Large Language Model Inference—0
Understanding Hidden Computations in Chain-of-Thought ReasoningCode0
Liquid: Language Models are Scalable Multi-modal GeneratorsCode4
Establishing Task Scaling Laws via Compute-Efficient Model Ladders—0
AL-QASIDA: Analyzing LLM Quality and Accuracy Systematically in Dialectal Arabic—0
ALMA: Alignment with Minimal Annotation—0
Aligned Music Notation and Lyrics TranscriptionCode0
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios—0
MISR: Measuring Instrumental Self-Reasoning in Frontier ModelsCode1
MIND: Effective Incorrect Assignment Detection through a Multi-Modal Structure-Enhanced Language ModelCode1
EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios—0
LL-ICM: Image Compression for Low-level Machine Vision via Large Vision-Language Model—0
A large language model-type architecture for high-dimensional molecular potential energy surfaces—0
Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection—0
EditScout: Locating Forged Regions from Diffusion-based Edited Images with Multimodal LLM—0
Benchmarking Harmonized Tariff Schedule Classification Models—0
From Language Models over Tokens to Language Models over Characters—0
Evaluating Language Models as Synthetic Data GeneratorsCode1
Language Model Meets Prototypes: Towards Interpretable Text Classification Models through Prototypical Networks—0
Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms—0
Video LLMs for Temporal Reasoning in Long Videos—0
Automatic detection of diseases in Spanish clinical notes combining medical language models and ontologies—0
Composed Image Retrieval for Training-Free Domain ConversionCode1
Who Brings the Frisbee: Probing Hidden Hallucination Factors in Large Vision-Language Model via Causality Analysis—0
PERL: Pinyin Enhanced Rephrasing Language Model for Chinese ASR N-best Error Correction—0
Scaling Inference-Time Search with Vision Value Model for Improved Visual ComprehensionCode1
FANAL -- Financial Activity News Alerting Language Modeling Framework—0
A surprisal oracle for when every layer countsCode0
Intent-driven In-context Learning for Few-shot Dialogue State Tracking—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