arXiv:2511. 02627v3 Announce Type: replace Abstract: We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse compositional spatial reasoning ability.
By Lachlan McPheat, Navdeep Kaur, Robert Blackwell, Alessandra Russo, Anthony G. Cohn, Pranava Madhyastha
arXiv:2606. 04381v1 Announce Type: cross Abstract: Recent large language models (LLMs) often appear to exhibit spatial reasoning ability; however, this capability is largely \emph{symbolic}, arising from pattern matching over spatial language rather than true \emph{geometric} reasoning over space.
By Chen Chu, Bita Azarijoo, Li Xiong, Khurram Shafique, Cyrus Shahabi
Recent large language models (LLMs) often appear to exhibit spatial reasoning ability; however, this capability is largely \emph{symbolic}, arising from pattern matching over spatial language rather than true \emph{geometric} reasoning over space. Because LLMs operate on discrete tokens, they lack native support for continuous spatial representations, explicit geometric computation, and structured spatial operators.
arXiv:2608. 03882v1 Announce Type: cross Abstract: Geospatial reasoning, i.
By Martin B\"ockling, Elizaveta Nosova, Heiko Paulheim, Andreea Iana
arXiv:2606. 31285v1 Announce Type: new Abstract: Human reasoning is inherently multimodal: when problems become difficult, we rarely think in words alone.
By Shreya Rajpal, Tanawan Premsri, Parisa Kordjamshidi
arXiv:2606.31285v3 Announce Type: replace
Abstract: Human reasoning is inherently multimodal: when problems become difficult, we rarely think in words alone. We often externalize our reasoning by ske...
By Shreya Rajpal, Tanawan Premsri, Parisa Kordjamshidi