Papers by Quan Pham
Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages (2024.acl-long)
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| Challenge: | Multilingual neural machine translation systems learn to map sentences of different languages into a common representation space. |
| Approach: | They propose a setup where we decouple learning of vocabulary and syntax and train to translate while keeping those word representations frozen. |
| Outcome: | The proposed setup achieves near parity with a supervised setting on the TED domain with varying number of languages seen by the encoder. |
HiGraAgent: Dual-Agent Adaptive Reasoning over Hierarchical Knowledge Graph for Open Domain Multi-hop Question Answering (2026.findings-eacl)
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| Challenge: | Existing approaches to multi-hop question answering lack a robust and flexible approach to QA . prior work showed compositionality gap persists even for Large Language Models . |
| Approach: | They propose a framework that unifies graph-based retrieval with adaptive reasoning . HiGraAgent uses a hierarchical knowledge Graph with entity alignment . |
| Outcome: | The proposed framework outperforms the strongest graph-based method on hotpotQA, 2WikiMultihopQA, and MuSiQue. |