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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 10601–10650 of 17610 papers

TitleStatusHype
SLM: Bridge the thin gap between speech and text foundation models—0
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games—0
Finding Pragmatic Differences Between Disciplines—0
Dynamic Demonstrations Controller for In-Context LearningCode0
UPAR: A Kantian-Inspired Prompting Framework for Enhancing Large Language Model Capabilities—0
LoRA ensembles for large language model fine-tuning—0
Split and Merge: Aligning Position Biases in LLM-based Evaluators—0
Telling Stories for Common Sense Zero-Shot Action RecognitionCode0
Self-Specialization: Uncovering Latent Expertise within Large Language Models—0
LLM-grounded Video Diffusion Models—0
Learning to Rewrite Prompts for Personalized Text Generation—0
Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback—0
Enhancing Code-switching Speech Recognition with Interactive Language Biases—0
A Large Language Model Approach to Educational Survey Feedback Analysis—0
Chatmap : Large Language Model Interaction with Cartographic Data—0
Augmenting LLMs with Knowledge: A survey on hallucination prevention—0
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language ModelsCode0
Hierarchical Cross-Modality Knowledge Transfer with Sinkhorn Attention for CTC-based ASR—0
Unsupervised Pretraining for Fact Verification by Language Model DistillationCode0
Language models in molecular discovery—0
Large Language Model Soft Ideologization via AI-Self-Consciousness—0
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language ModelsCode0
Large Language Model Routing with Benchmark Datasets—0
Borges and AI—0
Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative AnalysisCode0
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition—0
Robust Stance Detection: Understanding Public Perceptions in Social Media—0
Robustness of the Random Language Model—0
Large Language Model Alignment: A Survey—0
MSG-BART: Multi-granularity Scene Graph-Enhanced Encoder-Decoder Language Model for Video-grounded Dialogue Generation—0
XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection—0
Unsupervised Accent Adaptation Through Masked Language Model Correction Of Discrete Self-Supervised Speech Units—0
Cluster Language Model for Improved E-Commerce Retrieval and Ranking: Leveraging Query Similarity and Fine-Tuning for Personalized Results—0
Guess & Sketch: Language Model Guided Transpilation—0
Connecting Speech Encoder and Large Language Model for ASR—0
Introducing DictaLM -- A Large Generative Language Model for Modern Hebrew—0
Aligning Large Multimodal Models with Factually Augmented RLHF—0
Analyzing the Efficacy of an LLM-Only Approach for Image-based Document Question Answering—0
pLMFPPred: a novel approach for accurate prediction of functional peptides integrating embedding from pre-trained protein language model and imbalanced learning—0
Physics of Language Models: Part 3.2, Knowledge Manipulation—0
On the Relation between Internal Language Model and Sequence Discriminative Training for Neural Transducers—0
Towards General-Purpose Text-Instruction-Guided Voice Conversion—0
Keeping in Time: Adding Temporal Context to Sentiment Analysis Models—0
Substituting Data Annotation with Balanced Updates and Collective Loss in Multi-label Text ClassificationCode0
Cross-modal Alignment with Optimal Transport for CTC-based ASR—0
EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria—0
I-AI: A Controllable & Interpretable AI System for Decoding Radiologists' Intense Focus for Accurate CXR DiagnosesCode0
Calibrating LLM-Based EvaluatorCode0
Enhancing Student Performance Prediction on Learnersourced Questions with SGNN-LLM Synergy—0
An In-depth Survey of Large Language Model-based Artificial Intelligence Agents—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