mlsanityData to 14 Oct 2026

Who Is Left of Whom? Tracing Spatial Evidence and Role Binding in Relative-Position Reasoning

arXiv 2609.35486 ↗First posted 28 Sep 2026cs.CL cs.CVcited by 0

On the map: LLM reasoning → Spatial and embodied reasoning

Abstract (arXiv)

High instance-level accuracy can mask inconsistencies in spatial reasoning when objects exchange positions or their roles are reversed in the query. The internal representations supporting relative-position reasoning remain poorly understood. We investigate two complementary components of this process: tracking object locations in the input and representing their query roles. Across three VLMs with visual or textual inputs and their language-model backbones, activation patching reveals a staged progression from early-layer source representations through intermediate-layer query-object representations to late-layer answer states. Targeted interventions further establish causal links along this progression: manipulating source-side representations shifts location information at query-object mentions and ultimately alters relation predictions. Beyond object-location information, we also identify a stable query-side direction associated with the roles of the two objects in the comparison. Steering along directions estimated on synthetic scenes generalizes to natural-image benchmarks, improving accuracy and both forms of paired consistency in most settings without retraining. Our findings reveal complementary components of relational reasoning across visual and textual settings and show how targeted interventions can improve the consistency of models' behavior.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning. Builds on 43 of its 50 references that are in the map. First posted on arXiv 28 Sep 2026.

Builds on

43 of 50 references.

Closest ancestors · 12

Same direction, newest first

  1. 2026SpatialText: A Pure-Text Cognitive Benchmark for Spatial Understanding in Large Language Models3 Mar
  2. 2026Linear Mechanisms for Spatiotemporal Reasoning in Vision Language Models18 Jan
  3. 2025Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes8 Sep
  4. 2025OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models3 Jun
  5. 2025Beyond Semantics: Rediscovering Spatial Awareness in Vision-Language Models21 Mar
  6. 2025Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas3 Mar
  7. 2024Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces18 Dec
  8. 20243DSRBench: A Comprehensive 3D Spatial Reasoning Benchmark10 Dec
  9. 2024SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities22 Jan
  10. 2023What's "up" with vision-language models? Investigating their struggle with spatial reasoning30 Oct
  11. 2022Visual Spatial Reasoning30 Apr
  12. 2022StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts18 Apr

Other references · 31

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,510
  3. 2023Sparse Autoencoders Find Highly Interpretable Features in Language Modelscited by 1,420
  4. 2023Steering Language Models With Activation Engineeringcited by 922
  5. 2021Probing Classifiers: Promises, Shortcomings, and Advancescited by 876
  6. 2023The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasetscited by 712
  7. 2022When and why vision-language models behave like bags-of-words, and what to do about it?cited by 610
  8. 2022Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Spacecited by 532
  9. 2023Towards Best Practices of Activation Patching in Language Models: Metrics and Methodscited by 359
  10. 2015Towards AI-Complete Question Answering: A Set of Prerequisite Toy Taskscited by 314
  11. 2022Extracting Latent Steering Vectors from Pretrained Language Modelscited by 225
  12. 2023Interpreting CLIP's Image Representation via Text-Based Decompositioncited by 196
19 more
  1. 2024Towards Interpreting Visual Information Processing in Vision-Language Modelscited by 122
  2. 2024EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Modelscited by 107
  3. 2024Interpreting and Editing Vision-Language Representations to Mitigate Hallucinationscited by 104
  4. 2021SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoningcited by 77
  5. 2025V-STaR: Benchmarking Video-LLMs on Video Spatio-Temporal Reasoningcited by 68
  6. 2023Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIPcited by 62
  7. 2024Understanding Information Storage and Transfer in Multi-modal Large Language Modelscited by 49
  8. 2024What Do VLMs NOTICE? A Mechanistic Interpretability Pipeline for Gaussian-Noise-free Text-Image Corruption and Evaluationcited by 30
  9. 2024MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Modelcited by 26
  10. 2026ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loopcited by 26
  11. 2024Mechanistic?cited by 25
  12. 2025Multimodal Language Models See Better When They Look Shallowercited by 23
  13. 2026Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?cited by 19
  14. 2026LatentLens: Revealing Highly Interpretable Visual Tokens in LLMscited by 15
  15. 2025Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Imagescited by 13
  16. 2025V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Modelscited by 8
  17. 2024MINER: Mining the Underlying Pattern of Modality-Specific Neurons in Multimodal Large Language Modelscited by 7
  18. 2026Can LLMs See Without Pixels? Benchmarking Spatial Intelligence from Textual Descriptionscited by 7
  19. 2026Pathways of Visual Information Flow in Vision-Language Modelscited by 5

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  3. 2026When More Is Less: A Systematic Analysis of Spatial and Commonsense Information for Visual Spatial Reasoning
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  7. 2022What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning
  8. 2025Reasoning Path and Latent State Analysis for Multi-view Visual Spatial Reasoning: A Cognitive Science Perspective