7 citations · 14 across the 8 of their papers we have counts for
8 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…
Extract Free Dense Misalignment from CLIP
JeongYeon Nam, Jinbae Im, Wonjae Kim +1
Recent vision-language foundation models still frequently produce outputs misaligned with their inputs, evidenced by object hallucination in captioning and prompt misalignment in t…
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…
SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities
Hyunjong Ok, Taeho Kil, Sukmin Seo +1
Recent advances in named entity recognition (NER) have pushed the boundary of the task to incorporate visual signals, leading to many variants, including multi-modal NER (MNER) or…
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…
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models
Geewook Kim, Hodong Lee, Daehee Kim +7
Recent advances in Large Language Models (LLMs) have stimulated a surge of research aimed at extending their applications to the visual domain. While these models exhibit promise i…
Towards Unified Scene Text Spotting based on Sequence Generation
Taeho Kil, Seonghyeon Kim, Sukmin Seo +2
Sequence generation models have recently made significant progress in unifying various vision tasks. Although some auto-regressive models have demonstrated promising results in end…
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting
Seonghyeon Kim, Seung Shin, Yoonsik Kim +6
Recent end-to-end scene text spotters have achieved great improvement in recognizing arbitrary-shaped text instances. Common approaches for text spotting use region of interest poo…