SOTAVerified

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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7401–7450 of 17610 papers

TitleStatusHype
Wiping out the limitations of Large Language Models -- A Taxonomy for Retrieval Augmented Generation—0
SNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models—0
BOTS-LM: Training Large Language Models for Setswana—0
Large Language Model Aided QoS Prediction for Service Recommendation—0
Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation—0
Modelling Visual Semantics via Image Captioning to extract Enhanced Multi-Level Cross-Modal Semantic Incongruity Representation with Attention for Multimodal Sarcasm Detection—0
Progressively Label Enhancement for Large Language Model Alignment—0
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion—0
Effective Demonstration Annotation for In-Context Learning via Language Model-Based Determinantal Point Process—0
Defining and Evaluating Decision and Composite Risk in Language Models Applied to Natural Language Inference—0
A Novel Evaluation Framework for Image2Text Generation—0
Multi-Frame Vision-Language Model for Long-form Reasoning in Driver Behavior Analysis—0
MathLearner: A Large Language Model Agent Framework for Learning to Solve Mathematical Problems—0
Self-Emotion Blended Dialogue Generation in Social Simulation Agents—0
A Backbone for Long-Horizon Robot Task Understanding—0
The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines—0
Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer—0
SynesLM: A Unified Approach for Audio-visual Speech Recognition and Translation via Language Model and Synthetic Data—0
ABC Align: Large Language Model Alignment for Safety & Accuracy—0
Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation—0
Are Bigger Encoders Always Better in Vision Large Models?—0
Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model—0
UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation—0
Multi-Aspect Reviewed-Item Retrieval via LLM Query Decomposition and Aspect Fusion—0
Peptide Sequencing Via Protein Language Models—0
Towards Zero-Shot Annotation of the Built Environment with Vision-Language Models (Vision Paper)—0
Leveraging Large Language Models (LLMs) for Traffic Management at Urban Intersections: The Case of Mixed Traffic Scenarios—0
ExpertAF: Expert Actionable Feedback from Video—0
Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control—0
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts—0
MTA-CLIP: Language-Guided Semantic Segmentation with Mask-Text Alignment—0
SimpleLLM4AD: An End-to-End Vision-Language Model with Graph Visual Question Answering for Autonomous Driving—0
KemenkeuGPT: Leveraging a Large Language Model on Indonesia's Government Financial Data and Regulations to Enhance Decision Making—0
Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins—0
Intelligent Transformation: General Intelligence Theory—0
Finch: Prompt-guided Key-Value Cache Compression—0
Interpreting and learning voice commands with a Large Language Model for a robot system—0
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning—0
Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept—0
A federated large language model for long-term time series forecasting—0
Harvesting Textual and Structured Data from the HAL Publication Repository—0
Accelerating Large Language Model Inference with Self-Supervised Early Exits—0
Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline ApproachCode0
Decomposed Prompting to Answer Questions on a Course Discussion BoardCode0
Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification—0
Entropy, Thermodynamics and the Geometrization of the Language Model—0
Knesset-DictaBERT: A Hebrew Language Model for Parliamentary Proceedings—0
Label-Guided Prompt for Multi-label Few-shot Aspect Category Detection—0
Mimicking the Mavens: Agent-based Opinion Synthesis and Emotion Prediction for Social Media Influencers—0
Meltemi: The first open Large Language Model for Greek—0
Show:102550
← PrevPage 149 of 353Next →
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