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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7201–7250 of 17610 papers

TitleStatusHype
SPICED: Syntactical Bug and Trojan Pattern Identification in A/MS Circuits using LLM-Enhanced Detection—0
LLMs are Superior Feedback Providers: Bootstrapping Reasoning for Lie Detection with Self-Generated Feedback—0
Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized ModelsCode0
Enhancing SQL Query Generation with Neurosymbolic Reasoning—0
GNN: Graph Neural Network and Large Language Model for Data Discovery—0
Language Model Empowered Spatio-Temporal Forecasting via Physics-Aware Reprogramming—0
Selective Preference Optimization via Token-Level Reward Function Estimation—0
LIMP: Large Language Model Enhanced Intent-aware Mobility PredictionCode0
Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving—0
SpeechPrompt: Prompting Speech Language Models for Speech Processing Tasks—0
Predicting Affective States from Screen Text Sentiment—0
Learning to Plan Long-Term for Language Modeling—0
DrugAgent: Multi-Agent Large Language Model-Based Reasoning for Drug-Target Interaction Prediction—0
A Web-Based Solution for Federated Learning with LLM-Based Automation—0
CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition—0
Context-Aware Temporal Embedding of Objects in Video Data—0
In-Context Learning with Reinforcement Learning for Incomplete Utterance Rewriting—0
Can You Trust Your Metric? Automatic Concatenation-Based Tests for Metric Validity—0
Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMsCode0
Implicit Sentiment Analysis Based on Chain of Thought Prompting—0
Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards—0
Enhancing Multi-hop Reasoning through Knowledge Erasure in Large Language Model Editing—0
FIDAVL: Fake Image Detection and Attribution using Vision-Language ModelCode0
FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy DistillationCode0
TRRG: Towards Truthful Radiology Report Generation With Cross-modal Disease Clue Enhanced Large Language Model—0
Multi-tool Integration Application for Math Reasoning Using Large Language Model—0
Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimization—0
MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model—0
Vintern-1B: An Efficient Multimodal Large Language Model for Vietnamese—0
Video Emotion Open-vocabulary Recognition Based on Multimodal Large Language Model—0
What are the limits of cross-lingual dense passage retrieval for low-resource languages?—0
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model—0
A Quick, trustworthy spectral knowledge Q&A system leveraging retrieval-augmented generation on LLMCode0
GeoReasoner: Reasoning On Geospatially Grounded Context For Natural Language Understanding—0
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language ModelsCode0
Improving Speech Recognition Error Prediction for Modern and Off-the-shelf Speech Recognizers—0
Estimating Contribution Quality in Online Deliberations Using a Large Language Model—0
CaRDiff: Video Salient Object Ranking Chain of Thought Reasoning for Saliency Prediction with Diffusion—0
Design Principle Transfer in Neural Architecture Search via Large Language ModelsCode0
Automating Thought of Search: A Journey Towards Soundness and Completeness—0
SEA: Supervised Embedding Alignment for Token-Level Visual-Textual Integration in MLLMs—0
Swarm Intelligence in Geo-Localization: A Multi-Agent Large Vision-Language Model Collaborative Framework—0
Towards "Differential AI Psychology" and in-context Value-driven Statement Alignment with Moral Foundations Theory—0
WeQA: A Benchmark for Retrieval Augmented Generation in Wind Energy Domain—0
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding—0
Scaling Law with Learning Rate Annealing—0
Minor SFT loss for LLM fine-tune to increase performance and reduce model deviation—0
Unconditional Truthfulness: Learning Conditional Dependency for Uncertainty Quantification of Large Language Models—0
QPO: Query-dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning—0
Mistral-SPLADE: LLMs for better Learned Sparse RetrievalCode0
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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