---
title: "Who cites UnSeenTimeQA: Time-Sensitive — 10 citing papers"
description: "10 papers of the Elamur Research library cite «UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization», found in…"
canonical: "https://research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [UnSeenTimeQA: Time-Sensitive Question-Answering…](https://md.research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/) / cited by

# Who cites «UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization»

10 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 «UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization»](https://md.research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/)

1. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
2. **[IndustryAssetEQA: A Neurosymbolic Operational Intelligence System for Embodied Question Answering in Industrial Asset Maintenance](https://md.research.elamur.ai/free/en/papers/shyalika-2026-industryasseteqa-neurosymbolic-operational-intelligence-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chathurangi Shyalika, Dhaval C Patel, Amit Sheth*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/) — UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization