Papers by Jia-Huei Ju

3 papers
A Compare-and-contrast Multistage Pipeline for Uncovering Financial Signals in Financial Reports (2023.acl-long)

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Challenge: Recent advances in natural language processing (NLP) have included attempts to efficiently and effectively comprehend lengthy financial documents.
Approach: They propose a signal-highlighting task that analyzes relationships between financial reports . they also create and publicly release a human-annotated dataset for the task .
Outcome: The proposed pipeline is based on a human-annotated dataset and validates its effectiveness.
SERVAL: Surprisingly Effective Zero-Shot Visual Document Retrieval Powered by Large Vision and Language Models (2025.emnlp-main)

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Challenge: Visual Document Retrieval (VDR) relies on text-to-image retrieval using specialized bi-encoders . et al., 2022, 2024, 2021, 2023, 2026, 2030, 2040, 2050, 2060) document retrieval bridges human or artificial agents to the most relevant information, authors say .
Approach: They propose a zero-shot visual document retrieval method that uses bi-encoders . they propose 63.4% nDCG@5 for visual document capture and a reusable semantic proxy .
Outcome: The proposed method surpasses the strongest specialised multi-vector visual document encoder on the ViDoRe-v2 benchmark and scales similarly on MIRACL-VISION with broader multilingual coverage.
Controlled Retrieval-augmented Context Evaluation for Long-form RAG (2025.findings-emnlp)

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Challenge: Retrieval-augmented generation (RAG) enhances large language models by incorporating context retrieved from external knowledge sources.
Approach: They propose a Controlled Retrieval-aUgmented conteXt evaluation framework to directly assess retrieval-augmented contexts.
Outcome: The proposed framework uses human-written summaries to control the information scope of knowledge.

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