Papers by Maria Ganzha

1 papers
mllm-shap: A Shapley Value Explainability Platform for Text-Audio Multimodal Large Language Models (2026.acl-demo)

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Challenge: mllm-shap is an open-source Python platform for researchers and ML practitioners that extends Shapley value (SV) explainability from text-only large languagemodels to multimodal LLMs that process both text and audio.
Approach: They present a framework that extends Shapley value (SV) explainability from text-only large languagemodels to multimodal LLMs thatjointly process text and audio.
Outcome: mllm-shap is the first publicly available framework for complete, reproducible SV-based explainability of text-audioMLLMs.

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