70 citations · 357 across the 62 of their papers we have counts for
12 papers · 1 filter
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…
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,…
EMMM, Explain Me My Model! Explainable Machine Generated Text Detection in Dialogues
Angela Yifei Yuan, Haoyi Li, Soyeon Caren Han +1
The rapid adoption of large language models (LLMs) in customer service introduces new risks, as malicious actors can exploit them to conduct large-scale user impersonation through…
SPANER: Shared Prompt Aligner for Multimodal Semantic Representation
Thye Shan Ng, Caren Soyeon Han, Eun-Jung Holden
Recent advances in multimodal Parameter-Efficient Fine-Tuning (PEFT) have significantly improved performance on downstream tasks such as few-shot retrieval. However, most existing…
DocHop-QA: Towards Multi-Hop Reasoning over Multimodal Document Collections
Jiwon Park, Seohyun Pyeon, Jinwoo Kim +5
Despite rapid progress in large language models (LLMs), current QA benchmarks still overlook the core challenge of real-world scientific information seeking: synthesizing multimoda…
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…
VRD-IU: Lessons from Visually Rich Document Intelligence and Understanding
Yihao Ding, Soyeon Caren Han, Yan Li +1
Visually Rich Document Understanding (VRDU) has emerged as a critical field in document intelligence, enabling automated extraction of key information from complex documents across…
MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering
Shuo Yang, Siwen Luo, Soyeon Caren Han +1
Visual Question Answering (VQA) requires reasoning across visual and textual modalities, yet Large Vision-Language Models (LVLMs) often lack integrated commonsense knowledge, limit…
SPADE: Structured Prompting Augmentation for Dialogue Enhancement in Machine-Generated Text Detection
Haoyi Li, Angela Yifei Yuan, Soyeon Caren Han +1
The increasing capability of large language models (LLMs) to generate synthetic content has heightened concerns about their misuse, driving the development of Machine-Generated Tex…
A Training-Free Length Extrapolation Approach for LLMs: Greedy Attention Logit Interpolation (GALI)
Yan Li, Tianyi Zhang, Zechuan Li +1
Transformer-based Large Language Models (LLMs) struggle with inputs exceeding their training context window due to positional out-of-distribution (O.O.D.) issues that disrupt atten…
Graph-Based Multimodal Contrastive Learning for Chart Question Answering
Yue Dai, Soyeon Caren Han, Wei Liu
Chart question answering (ChartQA) is challenged by the heterogeneous composition of chart elements and the subtle data patterns they encode. This work introduces a novel joint mul…