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ChronoEdit
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Victor Mustar PRO
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I am on the model layer and focus on atomic tasks, so I don't get involved in product discussions. But this provocative article provoked the community quite a bit. The case in point is Claude Code, which happens to be my biggest productivity revolution since ChatGPT.
RAG predated TUI and agents. So to be fair it's quite an achievement to survive the AI evolution. But I feel it is overshadowed by context engineering in the agent era. How does everyone feel about this?
https://www.nicolasbustamante.com/p/the-rag-obituary-killed-by-agents
RAG predated TUI and agents. So to be fair it's quite an achievement to survive the AI evolution. But I feel it is overshadowed by context engineering in the agent era. How does everyone feel about this?
https://www.nicolasbustamante.com/p/the-rag-obituary-killed-by-agents
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🚀👁️🌟 New Research Alert - ICCV 2025 (Oral)! 🌟👁️🚀
📄 Title: Token Activation Map to Visually Explain Multimodal LLMs 🔝
📝 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.
👥 Authors: Yi Li, Hualiang Wang, Xinpeng Ding, Haonan Wang, and Xiaomeng Li
📅 Conference: ICCV, 19 – 23 Oct, 2025 | Honolulu, Hawai'i, USA 🇺🇸
📄 Paper: Token Activation Map to Visually Explain Multimodal LLMs (2506.23270)
📁 Repository: https://github.com/xmed-lab/TAM
🚀 ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
🚀 Added to the Multi-Modal Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/multi-modal-learning.md
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🔍 Keywords: #TokenActivationMap #TAM #CausalInference #VisualReasoning #Multimodal #Explainability #VisionLanguage #LLM #XAI #AI #ICCV2025 #ResearchHighlight
📄 Title: Token Activation Map to Visually Explain Multimodal LLMs 🔝
📝 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.
👥 Authors: Yi Li, Hualiang Wang, Xinpeng Ding, Haonan Wang, and Xiaomeng Li
📅 Conference: ICCV, 19 – 23 Oct, 2025 | Honolulu, Hawai'i, USA 🇺🇸
📄 Paper: Token Activation Map to Visually Explain Multimodal LLMs (2506.23270)
📁 Repository: https://github.com/xmed-lab/TAM
🚀 ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers
🚀 Added to the Multi-Modal Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/multi-modal-learning.md
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🔍 Keywords: #TokenActivationMap #TAM #CausalInference #VisualReasoning #Multimodal #Explainability #VisionLanguage #LLM #XAI #AI #ICCV2025 #ResearchHighlight
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