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πποΈπ New Research Alert - ICCV 2025 (Oral)! πποΈπ
π Title: Token Activation Map to Visually Explain Multimodal LLMs π
π Description: The Token Activation Map (TAM) is an advanced explainability method for multimodal LLMs. Using causal inference and a Rank Gaussian Filter, TAM reveals token-level interactions and eliminates redundant activations. The result is clearer, high-quality visualizations that enhance understanding of object localization, reasoning and multimodal alignment across models.
π₯ Authors: Yi Li, Hualiang Wang, Xinpeng Ding, Haonan Wang, and Xiaomeng Li
π
Conference: ICCV, 19 β 23 Oct, 2025 | Honolulu, Hawai'i, USA πΊπΈ
π Paper: https://huggingface.co/papers/2506.23270
π Repository: https://github.com/xmed-lab/TAM
π ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
π Added to the Multi-Modal Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/multi-modal-learning.md
π More Papers: more cutting-edge research presented at other conferences in the https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
π Keywords: #TokenActivationMap #TAM #CausalInference #VisualReasoning #Multimodal #Explainability #VisionLanguage #LLM #XAI #AI #ICCV2025 #ResearchHighlight
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