Papers by Sihong Xie

2 papers
MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity (2025.coling-main)

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Challenge: Existing RAG frameworks either indiscriminately perform retrieval or rely on rigid single-label classifiers to select retrieval methods.
Approach: They propose a framework that dynamically selects the most suitable retrieval strategy based on query complexity.
Outcome: The proposed framework achieves state-of-the-art results on multiple single-hop and multi-hop datasets while reducing retrieval costs.
CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models (2025.acl-long)

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Challenge: Existing benchmarks focus on “factual statements” that rephrase source materials, but ignore “cognitive statements” . evaluating and detecting "faithfulness hallucinations" remains challenging .
Approach: They propose a framework to assess faithfulness of cognitive statements and introduce a dataset to scale easily across models.
Outcome: The proposed framework assesses faithfulness of cognitive statements and scales easily across models.

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