---
title: "Who cites Question Answering Over — 75 citing papers"
description: "75 papers of the Elamur Research library cite «Question Answering Over Temporal Knowledge Graphs», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/saxena-2021-question-answering-over-temporal-knowledge/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/saxena-2021-question-answering-over-temporal-knowledge/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Question Answering Over Temporal Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/saxena-2021-question-answering-over-temporal-knowledge/) / cited by

# Who cites «Question Answering Over Temporal Knowledge Graphs»

75 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Question Answering Over Temporal Knowledge Graphs»](https://md.research.elamur.ai/free/en/papers/saxena-2021-question-answering-over-temporal-knowledge/)

1. **[Do Language Models Have a Common Sense regarding Time? Revisiting Temporal Commonsense Reasoning in the Era of Large Language Models](https://md.research.elamur.ai/free/en/papers/jain-2023-do-language-models-have-common/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Raghav Jain, Daivik Sojitra, Arkadeep Acharya, et al.*2023 · 67 citations*
2. **[ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events](https://md.research.elamur.ai/free/en/papers/islakoglu-2025-chronosense-exploring-temporal-understanding-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duygu Sezen Islakoglu, Jan-Christoph Kalo*2025 · 16 citations*
3. **[UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization](https://md.research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md Nayem Uddin, Amir Saeidi, Divij Handa, et al.*2025 · 14 citations*
4. **[RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models](https://md.research.elamur.ai/free/en/papers/gong-2025-rtqa-recursive-thinking-complex-temporal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoyan Gong, Juan Li, Zhiqiang Liu, et al.*2025 · 9 citations*
5. **[Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/gong-2026-temp-r1-unified-autonomous-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoyan Gong, Zhiqiang Liu, Songze Li, et al.*2026 · 4 citations*
6. **[Benchmarking Multilingual Temporal Reasoning in LLMs: The Temporal Reasoning Dataset](https://md.research.elamur.ai/free/en/papers/mazzia-2026-benchmarking-multilingual-temporal-reasoning-llms/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Vittorio Mazzia, Sandro Pollastrini, Davide Bernardi, et al.*2026 · 1 citation*
7. **[Temporal Evidence Chain for Temporal Knowledge Graph Question Answering with Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-temporal-evidence-chain-temporal-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihao Liu, Xiaofei Zhou, Bo Wang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/saxena-2021-question-answering-over-temporal-knowledge/) — Question Answering Over Temporal Knowledge Graphs
