---
title: "Who cites CAFE: Retrieval Head-based — 4 citing papers"
description: "4 papers of the Elamur Research library cite «CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document…"
canonical: "https://research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CAFE: Retrieval Head-based Coarse-to-Fine…](https://md.research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/) / cited by

# Who cites «CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability»

4 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability»](https://md.research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/)

1. **[Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering](https://md.research.elamur.ai/free/en/papers/tang-2025-unlocking-general-long-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Tang, Xiaolei Wang, Zhihao Lv, et al.*2025 · 19 citations*
2. **[POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/wang-2025-position-bias-mitigates-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yifei Wang, Feng Xiong, Yong Wang, et al.*2025 · 13 citations*

2 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/peng-2025-cafe-retrieval-head-based-coarse/) — CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability
