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Found 12 papers, 10 papers with code
Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark
This paper introduces the Open Ko-LLM Leaderboard and the Ko-H5 Benchmark as vital tools for evaluating Large Language Models (LLMs) in Korean.
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
We introduce SOLAR 10. 7B, a large language model (LLM) with 10. 7 billion parameters, demonstrating superior performance in various natural language processing (NLP) tasks.
Scale down Transformer by Grouping Features for a Lightweight Character-level Language Model
This paper introduces a method that efficiently reduces the computational cost and parameter size of Transformer.
Character Region Attention For Text Spotting
This architecture is formed by utilizing detection outputs in the recognizer and propagating the recognition loss through the detection stage.
CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks
We believe that our metrics can play a key role in developing and analyzing state-of-the-art text detection and recognition methods.
Few-shot Compositional Font Generation with Dual Memory
By utilizing the compositionality of compositional scripts, we propose a novel font generation framework, named Dual Memory-augmented Font Generation Network (DM-Font), which enables us to generate a high-quality font library with only a few samples.
On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention
Scene text recognition (STR) is the task of recognizing character sequences in natural scenes.
Ranked #3 on
Scene Text Recognition
on ICDAR 2003
Post-OCR parsing: building simple and robust parser via BIO tagging
Parsing textual information embedded in images is important for various down- stream tasks.
Optical Character Recognition
Optical Character Recognition (OCR)
CORD: A Consolidated Receipt Dataset for Post-OCR Parsing
OCR is inevitably linked to NLP since its final output is in text.
TedEval: A Fair Evaluation Metric for Scene Text Detectors
Despite the recent success of scene text detection methods, common evaluation metrics fail to provide a fair and reliable comparison among detectors.
Character Region Awareness for Text Detection
Scene text detection methods based on neural networks have emerged recently and have shown promising results.
Ranked #1 on
Scene Text Detection
on ICDAR 2013
(Precision metric)
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
Many new proposals for scene text recognition (STR) models have been introduced in recent years.
Ranked #7 on
Scene Text Recognition
on ICDAR 2003
