---
title: "Who cites Video Compression Commander: — 7 citing papers"
description: "7 papers of the Elamur Research library cite «Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large…"
canonical: "https://research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Video Compression Commander: Plug-and-Play…](https://md.research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/) / cited by

# Who cites «Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models»

7 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 «Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models»](https://md.research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/)

1. **[SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning](https://md.research.elamur.ai/free/en/papers/ji-2025-specvlm-enhancing-speculative-decoding-video/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yicheng Ji, Jun Zhang, Heming Xia, et al.*2025 · 10 citations*
2. **[HybridKV: Hybrid KV Cache Compression for Efficient Multimodal Large Language Model Inference](https://md.research.elamur.ai/free/en/papers/zeng-2026-hybridkv-hybrid-kv-cache-compression/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowen Zeng, Feiyang Ren, Jun Zhang, et al.*2026 · 4 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/) — Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models