
Research
PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
Researchers propose a new framework for AI pathology diagnosis that separates knowledge retrieval from evidence evaluation to reduce hallucinations. The system includes a novel experience-tracking mechanism to assess tool reliability over time, addressing critical accuracy concerns in medical AI applications.
Read full story at cs.AI updates on arXiv.org →V: · A: · D:
Related
Research
Nothing from Something: Can a Language Model Discover 0?
This arxiv paper uses the concept of zero as a test case for whether language models can engage in genuine mathematical ...
Research
Relational Structural Causal Models
Researchers have extended Pearl's structural causal models to settings where objects and their relations vary, addressin...
Research
A Definition of Good Explanations and the Challenges Explaining LLM Outputs
This arxiv paper proposes a formal definition of what constitutes a good explanation, drawing on counterfactual reasonin...