Research map / Large language models / Retrieval and knowledge
StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use TP-MANN instead of the strongest reported baseline | bAbI task 17 · bAbI task 17 | accuracy: 98.60$\pm$3.40 -> 99.88$\pm$0.10 | Helped |
| Use TP-MANN instead of STM | bAbI task 19 · bAbI task 19 | accuracy: 99.98$\pm$0.05 -> 99.98$\pm$0.04 | No clear effect |
| Use TP-MANN instead of TPR-RNN | StepGame · StepGame k=1–5, noisy test | mean accuracy: 40.81 -> 52.99 | Helped |
| Use TP-MANN instead of TPR-RNN | StepGame · StepGame k=6–10, noisy test | mean accuracy: 16.65 -> 24.53 | Helped |
| Increase the number of recurrent memory layers (ablation) | TP-MANN · StepGame, especially larger k | accuracy | Helped |
| Increase the number of recurrent memory layers (ablation) | TP-MANN · StepGame k=6–10, noisy test | accuracy | Helped |
Closest papers by meaning
- Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark (AAAI 2024 · similarity 0.92)
- ChainSpace: A Chained-Reasoning Paradigm for Spatial Intelligence (NeurIPS 2026 · similarity 0.88)
- Enhancing Spatial Reasoning Through Visual and Textual Thinking (AAAI 2026 · similarity 0.87)
- SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence (CVPR 2026 · similarity 0.87)
- SpatiaLQA: A Benchmark for Evaluating Spatial Logical Reasoning in Vision-Language Models (CVPR 2026 · similarity 0.87)
- Spatial-DISE: A Unified Benchmark for Evaluating Spatial Reasoning in Vision-Language Models (ICLR 2026 · similarity 0.87)
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