---
title: "Who cites StepGame: A New Benchmark for Robust Multi-Hop…"
description: "The papers of the Elamur Research library that cite «StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/shi-2022-stepgame-new-benchmark-robust-multi/cited-by/"
---
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# Who cites «StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts»

35 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/shi-2022-stepgame-new-benchmark-robust-multi/)

1. [Grid Spatial Understanding: A Dataset for Textual Spatial Reasoning over Grids, Embodied Settings, and Coordinate Structures](https://arxiv.org/abs/2603.17333) *— 2026 · arXiv:2603.17333*
2. [How Do LLMs and VLMs Understand Viewpoint Rotation Without Vision? An Interpretability Study](https://aclanthology.org/2026.acl-long.496/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [Multi-Constraint State Tracking with Negation: A Diagnostic Benchmark for LLM World Modeling](https://aclanthology.org/2026.acl-srw.119/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
4. [MultiGlobeQA: A Multilingual and Globally Diverse Benchmark for Geospatial Reasoning](https://arxiv.org/abs/2608.03882) *— 2026 · arXiv:2608.03882*
5. [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*
6. [AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking in Large Language Models](https://arxiv.org/abs/2505.17312) *— 2025 · arXiv:2505.17312*
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. [DecompSR: A dataset for decomposed analyses of compositional multihop spatial reasoning](https://arxiv.org/abs/2511.02627) *— 2025 · arXiv:2511.02627*
9. [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*
10. [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)*
11. [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*
12. [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)*
13. [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*
14. [Spatial Reasoning in Multimodal Large Language Models: A Survey of Tasks, Benchmarks and Methods](https://arxiv.org/abs/2511.15722) *— 2025 · arXiv:2511.15722*
15. [Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism](https://aclanthology.org/2025.findings-emnlp.893/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
16. [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*
17. [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*
18. [Consecutive Batch Model Editing with HooK Layers](https://aclanthology.org/2024.emnlp-main.765/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
19. [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*
20. [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*
21. [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)*
22. [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)*
23. [Stable LM 2 1.6B Technical Report](https://arxiv.org/abs/2402.17834) *— 2024 · arXiv:2402.17834*
24. [Teaching Probabilistic Logical Reasoning to Transformers](https://aclanthology.org/2024.findings-eacl.112/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
25. [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*
26. [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://arxiv.org/abs/2302.04023) *— 2023 · arXiv:2302.04023*
27. [Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text](https://aclanthology.org/2023.findings-acl.321/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
28. [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*
29. [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*
30. [Evaluating Spatial Understanding of Large Language Models](https://arxiv.org/abs/2310.14540) *— 2023 · arXiv:2310.14540*
31. [Lexical Entrainment for Conversational Systems](https://aclanthology.org/2023.findings-emnlp.22/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
32. [Rethinking Semi-supervised Learning with Language Models](https://aclanthology.org/2023.findings-acl.347/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
33. [Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language Understanding](https://aclanthology.org/2022.naacl-main.234/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
34. [Learning to Execute Actions or Ask Clarification Questions](https://aclanthology.org/2022.findings-naacl.158/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
35. [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*