---
title: "Who cites SPARTQA: A Textual Question Answering Benchmark…"
description: "The papers of the Elamur Research library that cite «SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [SPARTQA: A Textual Question Answering Benchmark…](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/) / cited by

# Who cites «SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning»

52 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)

1. [Can LLMs Learn to Map the World from Local Descriptions?](https://aclanthology.org/2026.acl-long.128/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [More Than Efficiency: Embedding Compression Improves Domain Adaptation in Dense Retrieval](https://aclanthology.org/2026.surgellm-1.24/) *— 2026 · Proceedings of the First Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era (SURGeLLM 2026)*
3. [MultiGlobeQA: A Multilingual and Globally Diverse Benchmark for Geospatial Reasoning](https://arxiv.org/abs/2608.03882) *— 2026 · arXiv:2608.03882*
4. [QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi](https://arxiv.org/abs/2605.18380) *— 2026 · arXiv:2605.18380*
5. [Reasoning Gets Harder for LLMs Inside A Dialogue](https://aclanthology.org/2026.acl-long.560/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
6. [TR-TEB: Turkish Text Embedding Benchmark](https://aclanthology.org/2026.lrec-1.862/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
7. [BIG-Bench Extra Hard](https://aclanthology.org/2025.acl-long.1285/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation](https://aclanthology.org/2025.coling-main.223/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
9. [Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation](https://aclanthology.org/2025.findings-acl.1342/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
10. [DrawingBench: Evaluating Spatial Reasoning and UI Interaction Capabilities of Large Language Models through Mouse-Based Drawing Tasks](https://arxiv.org/abs/2512.01174) *— 2025 · arXiv:2512.01174*
11. [FoREST: Frame of Reference Evaluation in Spatial Reasoning Tasks](https://aclanthology.org/2025.emnlp-main.1772/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
12. [L3GO: Language Agents with Chain-of-3D-Thoughts for Generating Unconventional Objects](https://aclanthology.org/2025.naacl-demo.37/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)*
13. [Large Language and Reasoning Models are Shallow Disjunctive Reasoners](https://aclanthology.org/2025.acl-long.433/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [Learning Language through Grounding](https://aclanthology.org/2025.naacl-tutorial.6/) *— 2025 · Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)*
15. [MMTEB: Massive Multilingual Text Embedding Benchmark](https://arxiv.org/abs/2502.13595) *— 2025 · arXiv:2502.13595*
16. [MastermindEval: A Simple But Scalable Reasoning Benchmark](https://arxiv.org/abs/2503.05891) *— 2025 · arXiv:2503.05891*
17. [Navigating Motion Agents in Dynamic and Cluttered Environments through LLM Reasoning](https://arxiv.org/abs/2503.07323) *— 2025 · arXiv:2503.07323*
18. [Neuro-symbolic Training for Reasoning over Spatial Language](https://aclanthology.org/2025.findings-naacl.128/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
19. [Overview of CCL25-Eval Task 1: The Fifth Spatial Cognition Evaluation (SpaCE2025)](https://aclanthology.org/2025.ccl-2.4/) *— 2025 · Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)*
20. [Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Spatial Reasoning](https://aclanthology.org/2025.findings-emnlp.217/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
21. [Spatial Reasoning in Multimodal Large Language Models: A Survey of Tasks, Benchmarks and Methods](https://arxiv.org/abs/2511.15722) *— 2025 · arXiv:2511.15722*
22. [Spatial Representation of Large Language Models in 2D Scene](https://aclanthology.org/2025.gem-1.3/) *— 2025 · Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM\texttwosuperior)*
23. [iVISPAR –- An Interactive Visual-Spatial Reasoning Benchmark for VLMs](https://aclanthology.org/2025.emnlp-main.1359/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
24. [seqBench: A Tunable Benchmark to Quantify Sequential Reasoning Limits of LLMs](https://aclanthology.org/2025.emnlp-main.1714/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
25. [Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark](https://arxiv.org/abs/2401.03991) *— 2024 · arXiv:2401.03991*
26. [Extracting and Following Paths for Robust Relational Reasoning with Large Language Models](https://arxiv.org/abs/2412.17963) *— 2024 · arXiv:2412.17963 · Transactions on Machine Learning Research, 2026*
27. [Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://aclanthology.org/2024.emnlp-main.148/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
28. [Mind”s Eye of LLMs: Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models](https://arxiv.org/abs/2404.03622) *— 2024 · arXiv:2404.03622*
29. [SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models](https://aclanthology.org/2024.acl-long.261/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Spatial and Temporal Language Understanding: Representation, Reasoning, and Grounding](https://aclanthology.org/2024.naacl-tutorials.6/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)*
31. [The Fourth Evaluation on Chinese Spatial Cognition](https://aclanthology.org/2024.ccl-3.14/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)*
32. [TopViewRS: Vision-Language Models as Top-View Spatial Reasoners](https://aclanthology.org/2024.emnlp-main.106/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
33. [tasksource: A Large Collection of NLP tasks with a Structured Dataset Preprocessing Framework](https://aclanthology.org/2024.lrec-main.1361/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
34. [基于参数高效微调与半监督学习的空间语义理解](https://aclanthology.org/2024.ccl-3.10/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)*
35. [A Benchmark for Reasoning with Spatial Prepositions](https://aclanthology.org/2023.emnlp-main.1015/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
36. [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://arxiv.org/abs/2302.04023) *— 2023 · arXiv:2302.04023*
37. [DepWiGNN: A Depth-wise Graph Neural Network for Multi-hop Spatial Reasoning in Text](https://aclanthology.org/2023.findings-emnlp.428/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
38. [Disentangling Extraction and Reasoning in Multi-hop Spatial Reasoning](https://aclanthology.org/2023.findings-emnlp.221/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
39. [Evaluating Spatial Understanding of Large Language Models](https://arxiv.org/abs/2310.14540) *— 2023 · arXiv:2310.14540*
40. [PromptDA: Label-guided Data Augmentation for Prompt-based Few Shot Learners](https://aclanthology.org/2023.eacl-main.41/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
41. [SpaCE2022中文空间语义理解评测任务数据集分析报告(A Quality Assessment Report of the Chinese Spatial Cognition Evaluation Benchmark)](https://aclanthology.org/2023.ccl-1.48/) *— 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics*
42. [SpaceNLI: Evaluating the Consistency of Predicting Inferences In Space](https://aclanthology.org/2023.naloma-1.2/) *— 2023 · Proceedings of the 4th Natural Logic Meets Machine Learning Workshop*
43. [Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings](https://aclanthology.org/2023.emnlp-main.596/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
44. [Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models](https://arxiv.org/abs/2310.00836) *— 2023 · arXiv:2310.00836*
45. [TraVLR: Now You See It, Now You Don”t! A Bimodal Dataset for Evaluating Visio-Linguistic Reasoning](https://aclanthology.org/2023.eacl-main.242/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
46. [Unifying Structure Reasoning and Language Model Pre-training for Complex Reasoning](https://arxiv.org/abs/2301.08913) *— 2023 · arXiv:2301.08913*
47. [Visual Spatial Reasoning](https://aclanthology.org/2023.tacl-1.37/) *— 2023*
48. [Zero-shot Probing of Pretrained Language Models for Geography Knowledge](https://aclanthology.org/2023.eval4nlp-1.5/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
49. [StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts](https://md.research.elamur.ai/free/en/papers/shi-2022-stepgame-new-benchmark-robust-multi/) *— our card · 2022 · arXiv:2204.08292*
50. [Things not Written in Text: Exploring Spatial Commonsense from Visual Signals](https://aclanthology.org/2022.acl-long.168/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
51. [Transfer Learning with Synthetic Corpora for Spatial Role Labeling and Reasoning](https://aclanthology.org/2022.emnlp-main.413/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
52. [Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding](https://aclanthology.org/2021.findings-emnlp.422/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*