Papers by Jenyuan Wang

2 papers
RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering (2024.emnlp-main)

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Challenge: Existing datasets for question answering based on retrieval augmented generation (RAG-QA) are either constructed using a single source corpus or consist of short extractive answers, which fall short of evaluating large language model (LLM) based RAG-QA systems on cross-domain generalization.
Approach: They propose a dataset that integrates short extractive answers from multiple documents into a single coherent narrative.
Outcome: The proposed dataset integrates short extractive answers from multiple documents into a single coherent narrative, covering 26K queries and large corpora across seven different domains.
Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains (2024.acl-short)

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Challenge: a new dataset examines whether fine-tuned metrics are robust to domain shifts between training and inference.
Approach: They use an annotated multidimensional quality metrics dataset to examine whether they are robust to domain shifts between training and inference.
Outcome: The proposed metrics exhibit a substantial performance drop in the unseen domain scenario compared to metrics that rely on the surface form and pre-trained metrics that are not fine-tuned on MT quality judgments.

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