Large-Scale Bitext Corpora Provide New Evidence for Cognitive Representations of Spatial Terms (2024.eacl-long)
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| Challenge: | Recent evidence suggests that there exist two classes of cognitive representations within the spatial terms of a language. |
| Approach: | They propose a pipeline for extracting, isolating, and aligning spatial terms from parallel text . they find evidence that variability in functional terms differs significantly from that of geometric terms . |
| Outcome: | The proposed pipeline extracts, isolates, and aligns spatial terms in basic locative constructions from parallel text. |
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| Challenge: | a new study examines whether large language models acquire embodied cognition and cultural conventions from training data . demonstratives are a natural lens for evaluating linguistic phenomena that reflect cultural variation . aaron e. duan and j. nà: "the complexity of the language model is a major challenge for LLMs" |
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| Challenge: | In this tutorial, we discuss the cutting-edge research results and existing challenges related to spatial language understanding including semantic annotations, existing corpora, symbolic and sub-symbolic representations, qualitative spatial reasoning, spatial common sense, deep and structured learning models. |
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Can LLMs Learn to Map the World from Local Descriptions? (2026.acl-long)
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| Challenge: | This tutorial provides an overview of cutting edge research on spatial and temporal language understanding. |
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| Challenge: | Recent work has re-surfaced a concern that has long plagued vision-language models: poor performance on simple tasks like attribute attachment, counting, etc. |
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