7 citations · 7 across the 6 of their papers we have counts for
6 papers
Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching
Jaewoo Park, Minyoung Lee, Sukmin Seo +11
Multimodal large language models (MLLMs) are increasingly used to make decisions for drones, but existing evaluations are mostly limited to simulation, to a single drone, and to ta…
Natural-Language Temporal Grounding in Hour-Long Videos is a Search Problem: A Benchmark and Empirical Decomposition
Sukmin Seo, Geewook Kim
Temporal grounding--returning the interval for a natural-language query over a video--is the language interface to long-form video, yet has been studied on short video…
CREPE: Coordinate-Aware End-to-End Document Parser
Yamato Okamoto, Youngmin Baek, Geewook Kim +5
In this study, we formulate an OCR-free sequence generation model for visual document understanding (VDU). Our model not only parses text from document images but also extracts the…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
SCOB: Universal Text Understanding via Character-wise Supervised Contrastive Learning with Online Text Rendering for Bridging Domain Gap
Daehee Kim, Yoonsik Kim, DongHyun Kim +3
Inspired by the great success of language model (LM)-based pre-training, recent studies in visual document understanding have explored LM-based pre-training methods for modeling te…
On Web-based Visual Corpus Construction for Visual Document Understanding
Donghyun Kim, Teakgyu Hong, Moonbin Yim +2
In recent years, research on visual document understanding (VDU) has grown significantly, with a particular emphasis on the development of self-supervised learning methods. However…