21 papers · 1 filter
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…
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…
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…
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…
Deep Learning based Visually Rich Document Content Understanding: A Survey
Yihao Ding, Soyeon Caren Han, Jean Lee +1
Visually Rich Documents (VRDs) play a vital role in domains such as academia, finance, healthcare, and marketing, as they convey information through a combination of text, layout,…
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…