---
title: "Who cites Gated Differentiable Working — 4 citing papers"
description: "4 papers of the Elamur Research library cite «Gated Differentiable Working Memory for Long-Context Language Modeling», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Gated Differentiable Working Memory for…](https://md.research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/) / cited by

# Who cites «Gated Differentiable Working Memory for Long-Context Language Modeling»

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 «Gated Differentiable Working Memory for Long-Context Language Modeling»](https://md.research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/)

1. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
2. **[a1: Steep Test-time Scaling Law via Environment Augmented Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-a1-steep-test-time-scaling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 2 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/mei-2026-gated-differentiable-working-memory-long/) — Gated Differentiable Working Memory for Long-Context Language Modeling
