---
title: "Who cites Turning Trash into Treasure: — 20 citing papers"
description: "20 papers of the Elamur Research library cite «Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token…"
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---
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# Who cites «Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling»

20 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling»](https://md.research.elamur.ai/free/en/papers/luo-2025-turning-trash-into-treasure-accelerating/)

1. **[LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation](https://md.research.elamur.ai/free/en/papers/liu-2026-logitspec-accelerating-retrieval-based-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Liu, Qitan Lv, Hao Li, et al.*2026 · 6 citations*
2. [**AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery arXiv:2604.05550**Yu Li, Chenyang Shao, Xinyang Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/li-2026-autosota-end-end-automated-research/)
3. **[LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification](https://md.research.elamur.ai/free/en/papers/yang-2026-longspec-long-context-lossless-speculative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Penghui Yang, Cunxiao Du, Fengzhuo Zhang, et al.*2026 · 5 citations*
4. **[RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-racer-retrieval-augmented-contextual-rapid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihong Zhang, Zuchao Li, Lefei Zhang, et al.*2026 · 1 citation*
5. **[MTP-RL: Acceleration of Reinforcement Learning Rollouts with Policy-Aligned Multi-Token Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-mtp-rl-acceleration-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ke Wang, Aohan Zeng, Zhengxiao Du, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/luo-2025-turning-trash-into-treasure-accelerating/) — Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling