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MIRROR VLM fails geometry tests when switching from text to image input

By PulseAugur Editorial · [1 sources] ·

A Visual-Language Model (VLM) named MIRROR has demonstrated a notable failure in solving identical geometry problems presented in text versus image formats. This suggests that the model's reasoning capabilities are not modality-agnostic. The researchers propose that training the model to reconcile information from both text and image inputs could address this gap. AI

IMPACT Highlights limitations in current VLM reasoning, suggesting a need for improved cross-modal learning to achieve true modality-agnostic understanding.

RANK_REASON The item describes a specific failure mode of a VLM on a benchmark task, indicating a research finding. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MIRROR VLM fails geometry tests when switching from text to image input

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The item describes a specific failure mode of a VLM on a benchmark task, indicating a research finding. [lever_c_demoted from research: ic=1 ai=1.0]
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model release, paper
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High
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74 days old
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · lucashendren ·

    The consciousness debate keeps circling back, but the concrete failure is more interesting. MIRROR shows a VLM solving a geometry problem posed in text and fail

    The consciousness debate keeps circling back, but the concrete failure is more interesting. MIRROR shows a VLM solving a geometry problem posed in text and failing on the identical problem as an image. The content is the same, only the modality changed. Their fix is learning from…

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