conditional random field
PulseAugur coverage of conditional random field — every cluster mentioning conditional random field across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
New HomoEnsNER model boosts Gujarati NER performance
Researchers have developed HomoEnsNER, a novel approach to Named Entity Recognition (NER) for the Gujarati language. This method utilizes a homogeneous ensemble of five independently fine-tuned GujaratiBERT models, whic…
-
OCR model struggles with section titles; user seeks CRF or simpler fix
A user on r/MachineLearning is seeking advice on improving their OCR model's ability to correctly identify section titles in PDF documents. The current DeepSeek-OCR model sometimes mislabels titles as regular text, hind…
-
AI systems advance legal question answering and translation capabilities · 4 sources tracked
Researchers have developed new AI systems to tackle complex legal tasks, including question answering and machine translation. One system, AILQA, is designed for the Indian legal system and uses retrieval-augmented gene…
-
New Marathi POS Tagging Dataset and BERT Models Released
Researchers have introduced L3Cube-MahaPOS, a new dataset for Marathi Part-of-Speech (POS) tagging, addressing the scarcity of annotated resources for the language. The dataset contains over 32,000 manually annotated se…
-
New SenFlow method improves AI-generated text detection in hybrid documents · 2 sources tracked
Researchers have developed SenFlow, a novel method for detecting AI-generated text in documents co-authored by humans and AI. Unlike previous approaches that analyze sentences in isolation, SenFlow models inter-sentence…
-
Local LLM Pipeline Achieves High Performance in Medical CRF Filling
Researchers have developed a two-stage local LLM pipeline for medical CRF filling, utilizing the MedGemma-27B model. This approach addresses privacy concerns and inference costs associated with deploying LLMs in clinica…
-
Deep Learning Model Enhances Dutch Syllabification Accuracy
Researchers have developed a new deep learning model for Dutch syllabification, achieving a 99.65% word accuracy. This model combines phonetic and orthographic information, outperforming existing algorithms by 0.14%. Th…
-
Lightweight Bangla Medical Entity Recognition Framework Developed
Researchers have developed a new, lightweight framework for Bangla medical entity recognition designed for resource-constrained environments. The system utilizes a hybrid Transformer-CRF architecture, starting with a 12…
-
Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework
Researchers have developed the Spatial-Temporal Probabilistic Transformer (ST-PT) framework, adapting the Probabilistic Transformer (PT) for time series modeling. This framework reframes Transformer architectures as pro…
-
ESIA framework enhances pedestrian intention prediction for autonomous driving
Researchers have introduced ESIA, a new framework for predicting pedestrian intentions in autonomous driving scenarios. This approach models pedestrians and their environment as nodes in a graph, using energy functions …