---
title: "Who cites Faster MoE LLM Inference for Extremely Large Models"
description: "8 papers of the Elamur Research library cite «Faster MoE LLM Inference for Extremely Large Models», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/yang-2026-faster-moe-llm-inference-extremely/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Faster MoE LLM Inference for Extremely Large…](https://md.research.elamur.ai/free/en/papers/yang-2026-faster-moe-llm-inference-extremely/) / cited by

# Who cites «Faster MoE LLM Inference for Extremely Large Models»

8 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1 with a page here, the most cited first · [← back to «Faster MoE LLM Inference for Extremely Large Models»](https://md.research.elamur.ai/free/en/papers/yang-2026-faster-moe-llm-inference-extremely/)

1. **[COMPEL: Compensated Mixture-of-Experts Pruning with Expert-Layer distribution](https://md.research.elamur.ai/free/en/papers/yoon-2026-compel-compensated-mixture-experts-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seohee Yoon, Yong Suk Choi*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/yang-2026-faster-moe-llm-inference-extremely/) — Faster MoE LLM Inference for Extremely Large Models