FIELD NOTES TOPIC

causality

5 notes, newest first.

  1. The Illusion of Visual Tool-Use: A Causal Audit of Thinking with Images

    Source note ·

    Researchers audit the effectiveness of using visual tools like crop-and-zoom in multimodal language models by creating a causal graph to separate observation-mediated paths from action-induced shortcuts. They find that…

  2. The Illusion of Visual Tool-Use: A Causal Audit of Thinking with Images

    Source note ·

    The study examines the 'thinking-with-images' paradigm used in multimodal Language Models (LLMs), which includes visual operations like crop-and-zoom. The research finds that these operations often result in minimal or…

  3. Solution of the Hempel's statistical ambiguity problem and Causal AI

    Source note ·

    The paper presents a solution to Hempel's statistical ambiguity problem in inductive-statistical inference by introducing the concept of Maximally Specific Causal Relationships (MSCRs). The MSCRs are derived from a…

  4. Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

    Source note ·

    This research paper discusses the need for better understanding and transparency in Artificial Intelligence (AI) used in healthcare, focusing on the explanatory process of Machine Learning models. It highlights that…

  5. OpenRCA 2.0: From Outcome Labels to Causal Process Supervision

    Source note ·

    The paper introduces OpenRCA 2.0, a new benchmark for root cause analysis (RCA) of large language models (LLMs). The benchmark includes step-wise causal annotations for LLMs and addresses the issue that existing…