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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 22512300 of 17610 papers

TitleStatusHype
Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language ModelsCode1
DirectorLLM for Human-Centric Video Generation0
A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation0
ConfliBERT: A Language Model for Political ConflictCode1
Disentangling Reasoning Tokens and Boilerplate Tokens For Language Model Fine-tuning0
Movie2Story: A framework for understanding videos and telling stories in the form of novel text0
Knowing Where to Focus: Attention-Guided Alignment for Text-based Person Search0
ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case StudyCode0
HarmonicEval: Multi-modal, Multi-task, Multi-criteria Automatic Evaluation Using a Vision Language Model0
Autonomous Microscopy Experiments through Large Language Model AgentsCode1
ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language ModelingCode1
GenX: Mastering Code and Test Generation with Execution Feedback0
EscapeBench: Pushing Language Models to Think Outside the BoxCode1
Large Language Model Enhanced Recommender Systems: A SurveyCode2
SongEditor: Adapting Zero-Shot Song Generation Language Model as a Multi-Task Editor0
On Enhancing Root Cause Analysis with SQL Summaries for Failures in Database Workload Replays at SAP HANA0
Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation0
LLM-SEM: A Sentiment-Based Student Engagement Metric Using LLMS for E-Learning Platforms0
CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers0
The Reliability Paradox: Exploring How Shortcut Learning Undermines Language Model Calibration0
On the Structural Memory of LLM AgentsCode0
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference0
Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration0
Task-Agnostic Language Model Watermarking via High Entropy Passthrough Layers0
Core Context Aware Attention for Long Context Language Modeling0
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training0
LMUnit: Fine-grained Evaluation with Natural Language Unit Tests0
iPrOp: Interactive Prompt Optimization for Large Language Models with a Human in the Loop0
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text GenerationCode0
Make Imagination Clearer! Stable Diffusion-based Visual Imagination for Multimodal Machine Translation0
DSGram: Dynamic Weighting Sub-Metrics for Grammatical Error Correction in the Era of Large Language ModelsCode0
Preference-Oriented Supervised Fine-Tuning: Favoring Target Model Over Aligned Large Language ModelsCode0
FocusChat: Text-guided Long Video Understanding via Spatiotemporal Information Filtering0
Uncertainty-Aware Hybrid Inference with On-Device Small and Remote Large Language Models0
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model ApproachCode0
SnakModel: Lessons Learned from Training an Open Danish Large Language ModelCode1
Track the Answer: Extending TextVQA from Image to Video with Spatio-Temporal CluesCode0
Large Language Models as Realistic Microservice Trace GeneratorsCode1
Next Token Prediction Towards Multimodal Intelligence: A Comprehensive SurveyCode3
Krony-PT: GPT2 compressed with Kronecker Products0
Endangered Alert: A Field-Validated Self-Training Scheme for Detecting and Protecting Threatened Wildlife on Roads and RoadsidesCode0
Private Yet Social: How LLM Chatbots Support and Challenge Eating Disorder Recovery0
AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power LawsCode0
A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges0
The Impact of Token Granularity on the Predictive Power of Language Model Surprisal0
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual DataCode2
Personalized LLM for Generating Customized Responses to the Same Query from Different UsersCode0
MERaLiON-SpeechEncoder: Towards a Speech Foundation Model for Singapore and Beyond0
OmniVLM: A Token-Compressed, Sub-Billion-Parameter Vision-Language Model for Efficient On-Device Inference0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified