Papers by Zhiyang Jia

2 papers
EfficientRAG: Efficient Retriever for Multi-Hop Question Answering (2024.emnlp-main)

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Challenge: Existing retrieval-augmented generation methods rely on multiple calls of large language models (LLMs) Large-language models lack knowledge underrepresented in training data and still face hallucinations.
Approach: They propose an efficient retriever for multi-hop question answering that generates new queries iteratively without the need for LLM calls.
Outcome: The proposed method surpasses existing methods on three open-domain multi-hop question-answering datasets.
VoxMind: An End-to-End Agentic Spoken Dialogue System (2026.acl-long)

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Challenge: Existing research on end-to-end spoken dialogue models has focused on core perception and generation, with limited exploration of tool-augmented extensions.
Approach: They propose a framework to equip end-to-end spoken dialogue models with comprehensive agentic abilities by leveraging a 470-hour AgentChat dataset.
Outcome: The proposed framework outperforms Gemini-2.5-Pro on spoken agent tasks while maintaining general conversational quality.

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