{"schema_version":"onlylabs.public_signal.v1","title":"Google (DeepMind / Gemini) Repo: google-deepmind/polaris-bench","description":"Google (DeepMind / Gemini) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/6d9511ba-e40d-4c88-b478-4ea105d78732","json_url":"https://onlylabs.fyi/signals/6d9511ba-e40d-4c88-b478-4ea105d78732/signal.json","generated_at":"2026-09-11T19:07:13.638Z","evidence_latest_fetched_at":"2026-09-11T07:03:14.200926+00:00","signal_first_seen_at":"2026-09-11T07:00:34.114614+00:00","org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/google-deepmind","dossier_json_url":"https://onlylabs.fyi/labs/google-deepmind/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/6d9511ba-e40d-4c88-b478-4ea105d78732","signal_json":"https://onlylabs.fyi/signals/6d9511ba-e40d-4c88-b478-4ea105d78732/signal.json","source":"https://github.com/google-deepmind/polaris-bench","lab_dossier":"https://onlylabs.fyi/labs/google-deepmind","lab_dossier_json":"https://onlylabs.fyi/labs/google-deepmind/dossier.json","analysis":"https://onlylabs.fyi/analysis/google-deepmind","analysis_json":"https://onlylabs.fyi/analysis/google-deepmind/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/google-deepmind/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Google (DeepMind / Gemini) published google-deepmind/polaris-bench (Python). 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In this work, we identify a pervasive vulnerability: **the Cartesian Shortcut**. The Cartesian Shortcut Standard visual reasoning benchmarks are predominantly structured around orthogonal, grid-based Cartesian layouts. We find that state-of-the-art models systematically exploit this structure: rather than performing true visual-spatial reasoning, they discretize 2D images into explicit textual coordinates (such as row and column indices) and offload spatial deduction onto pure text-based reasoning. 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