Papers by Meiru Zhang
Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck (2026.acl-long)
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| Challenge: | Existing studies have identified a position bias in Large Language Models that causes them to overlook information at certain positions. |
| Approach: | They propose a semantic probe to disentangle position bias in Large Language Models . they propose MFAI to steer attention towards selected positions . |
| Outcome: | The proposed model can locate and integrate information at certain positions even in noisy, long-context settings. |
Can We Instruct LLMs to Compensate for Position Bias? (2024.findings-emnlp)
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| Challenge: | Recent studies reveal that position bias in large language models (LLMs) leads to difficulty in accessing information retrieved from the retriever. |
| Approach: | They propose to direct LLMs to allocate more attention towards a selected segment of the context through prompting. |
| Outcome: | The proposed approach improves the performance of large language models by promoting instruction with an exact document index. |