Papers by Keer Xu
PRiSM: Benchmarking Phone Realization in Speech Models (2026.acl-long)
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Shikhar Bharadwaj, Chin-Jou Li, Yoonjae Kim, Kwanghee Choi, Eunjung Yeo, Ryan Soh-Eun Shim, Hanyu Zhou, Brendon Boldt, Karen Rosero, Kalvin Chang, Darsh Agrawal, Keer Xu, Chao-Han Huck Yang, Jian Zhu, Shinji Watanabe, David R. Mortensen
| Challenge: | Existing evaluations of phone recognition systems only measure surface-level transcription accuracy. |
| Approach: | They propose to standardize transcription-based evaluation and assess downstream utility in clinical, educational, and multilingual settings with transcription and representation probes. |
| Outcome: | The proposed system outperforms LALMs in clinical, educational, and multilingual settings. |
GLAMR: Augmenting AMR with GL-VerbNet Event Structure (2024.lrec-main)
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Jingxuan Tu, Timothy Obiso, Bingyang Ye, Kyeongmin Rim, Keer Xu, Liulu Yue, Susan Windisch Brown, Martha Palmer, James Pustejovsky
| Challenge: | Abstract Meaning Representation (AMR) is a general-purpose semantic encoding for language. |
| Approach: | They propose an AMR interpretation of Generative Lexicon semantic components using a verb-net-encoded verb-node graph. |
| Outcome: | The proposed extension is compatible with current AMR specification and can be automated. |
Linguistically Conditioned Semantic Textual Similarity (2024.acl-long)
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| Challenge: | Semantic textual similarity (STS) is a fundamental NLP task that measures the semantic similarity between two sentences. |
| Approach: | They propose to use a conditional STS dataset to measure sentences’ similarity conditioned on a certain aspect to reduce the inherent ambiguity posed by the sentences. |
| Outcome: | The proposed method improves the performance over baselines on the C-STS dataset with over 80% F1 score. |