17 papers
DocHop-QA: Towards Multi-Hop Reasoning over Multimodal Document Collections
Jiwon Park, Seohyun Pyeon, Jinwoo Kim +4
Despite rapid progress in large language models (LLMs), current QA benchmarks still overlook the core challenge of real-world scientific information seeking: synthesizing multimoda…
MUSEKG: A Knowledge Graph Over Museum Collections
Jinhao Li, Jianzhong Qi, Soyeon Caren Han +1
Digitisation in the cultural heritage sector has produced large but fragmented repositories of museum collection data, spanning structured catalogue records, images, and unstructur…
MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Models
Suchan Lee, Jihoon Choi, Sohyeon Lee +4
Recent advances have investigated the use of pretrained large language models (LLMs) for time-series forecasting by aligning numerical inputs with LLM embedding spaces. However, ex…
UniCast: A Unified Framework for Instance-Conditioned Multimodal Time-Series Forecasting
Sehyuk Park, Soyeon Caren Han, Eduard Hovy
Time series forecasting underpins applications in finance, healthcare, and environmental monitoring. Despite the success of Time Series Foundation Models (TSFMs), existing approach…
SynJAC: Synthetic-data-driven Joint-granular Adaptation and Calibration for Domain Specific Scanned Document Key Information Extraction
Yihao Ding, Soyeon Caren Han, Zechuan Li +1
Visually Rich Documents (VRDs), comprising elements such as charts, tables, and paragraphs, convey complex information across diverse domains. However, extracting key information f…
SynDoc: A Hybrid Discriminative-Generative Framework for Enhancing Synthetic Domain-Adaptive Document Key Information Extraction
Yihao Ding, Soyeon Caren Han, Yanbei Jiang +3
Domain-specific Visually Rich Document Understanding (VRDU) presents significant challenges due to the complexity and sensitivity of documents in fields such as medicine, finance,…