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Omni-LLMs struggle to express non-textual knowledge, new strategy aims to fix

By PulseAugur Editorial · [2 sources] ·

Researchers have identified a phenomenon in Omni-modal Large Language Models (Omni-LLMs) where the models can perceive information from non-textual modalities like vision and audio but struggle to express it. This "knows-but-cannot-say" issue is investigated using Token-level Modality Alignment (TMA), which reveals that non-textual representations receive less attention. To address this, a new strategy called OmniCatalyst is proposed, which augments input with self-generated text to make non-textual knowledge more accessible. This approach has shown consistent performance improvements across multiple Omni-LLMs. AI

IMPACT This research could lead to more capable multimodal AI systems that can better integrate and communicate information from diverse data sources.

RANK_REASON The cluster describes a research paper detailing a new phenomenon and proposed method for Omni-modal LLMs.

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Omni-LLMs struggle to express non-textual knowledge, new strategy aims to fix

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The cluster describes a research paper detailing a new phenomenon and proposed method for Omni-modal LLMs.
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12 days old
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Na Min An, Taekyung Kim, Jaemyung Yu, Hyunjung Shim, Dongyoon Han ·

    Omni-Modal LLMs Know More Than They Say

    arXiv:2610.16135v1 Announce Type: cross Abstract: Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language, enabling a broader range of multimodal tasks. Yet we find that these models of…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Omni-Modal LLMs Know More Than They Say

    Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language, enabling a broader range of multimodal tasks. Yet we find that these models often fail to express information from non-textual m…

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