---
title: "Who cites FBS: Modeling Native Parallel — 10 citing papers"
description: "10 papers of the Elamur Research library cite «FBS: Modeling Native Parallel Reading inside a Transformer», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/wang-2026-fbs-modeling-native-parallel-reading/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2026-fbs-modeling-native-parallel-reading/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [FBS: Modeling Native Parallel Reading inside a…](https://md.research.elamur.ai/free/en/papers/wang-2026-fbs-modeling-native-parallel-reading/) / cited by

# Who cites «FBS: Modeling Native Parallel Reading inside a Transformer»

10 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «FBS: Modeling Native Parallel Reading inside a Transformer»](https://md.research.elamur.ai/free/en/papers/wang-2026-fbs-modeling-native-parallel-reading/)

1. **[Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-rag-mitigating-retrieval-permutation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianchi Zhang, Hainan Zhang, Liang Pang, et al.*2026 · 27 citations*
2. **[FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/jiang-2026-foe-forest-errors-makes-first/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kehan Jiang, Haonan Dong, Zhaolu Kang, et al.*2026 · 15 citations*
3. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
4. **[PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-perm-psychology-grounded-empathetic-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengbing Wang, Wuqiang Zheng, Yang Zhang, et al.*2026 · 8 citations*
5. **[PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-pdtrim-targeted-pruning-prefill-decode/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zhang, Lyu Mengsi, Zhuo Chen, et al.*2026 · 6 citations*
6. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Lyu Mengsi, Chenrui He, et al.*2026 · 6 citations*
7. **[HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance](https://md.research.elamur.ai/free/en/papers/zhang-2026-hyperadalora-accelerating-lora-rank-allocation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Zhenjia Li, Yifan Gao, et al.*2026 · 5 citations*
8. **[StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-streammeco-long-term-agent-memory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junxi Wang, Te Sun, Jiayi Zhu, et al.*2026 · 3 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/wang-2026-fbs-modeling-native-parallel-reading/) — FBS: Modeling Native Parallel Reading inside a Transformer