Papers by Jenyuan Wang
RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering (2024.emnlp-main)
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Rujun Han, Yuhao Zhang, Peng Qi, Yumo Xu, Jenyuan Wang, Lan Liu, William Yang Wang, Bonan Min, Vittorio Castelli
| 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. |