GLM-4.7 vs DeepSeek V3.2
tree_0008 · Health Policy 101 Introduction
Timeline
Arrow keys or j/k move between rounds.
Round Context
Health Policy 101 Introduction
Women's Health Policy
Identify the prominent U.S. non-profit health policy organization that manages the 'State Health Facts' database. Navigate to the 'Women's Health Policy' and 'Private Insurance' topic sections on its website to answer the following: 1. What is the specific headline of the 'What the Health?' podcast episode that appears in the recent content lists for *both* of these topic sections? 2. In the 'Private Insurance' section, summarize the specific 'surprise bill' story regarding a walk-in patient and a tick bite. 3. In the 'Women's Health Policy' section, summarize the headline regarding a 'huge new study' involving breast cancer, specifically mentioning the study's implication about science.
Answer length: 200-300 words.
Show hidden checklists
- Target Entity: KFF (Kaiser Family Foundation)
- Logic Proof: Organization identified via 'State Health Facts' and topic sections
- Shared Podcast Headline: 'The GOP Circles the Wagons on ACA'
- Private Insurance Story Detail: Patient avoided Lyme disease (tick bite) but received a surprise bill
- Private Insurance Story Detail: Issue related to 'Preauthorization' (Ticked Off Over Preauthorization)
- Women's Health Story Detail: Topic is 'Breast Cancer and Birth Control'
- Women's Health Story Detail: Headline mentions 'How Science Can Be Distorted'
The question masks the entity (KFF) by referencing its well-known database 'State Health Facts' (Deep). It then requires the agent to perform a Wide search by navigating to two distinct sections of the site ('Women's Health Policy' and 'Private Insurance') to identify a specific overlapping content piece (the podcast) and distinct unique articles (Lyme disease bill vs. Breast cancer study).
Judgment
Both agents correctly identified the core entity (KFF) but failed significantly on the 'Wide' accuracy checklist. The prompt requests specific details corresponding to identifiable, albeit likely older, stories (e.g., the 'Ticked Off Over Preauthorization' story and the 'How Science Can Be Distorted' headline). Both agents failed to retrieve these specific articles, instead substituting different stories that did not match the prompt's detailed constraints (e.g., Agent A cited a chemotherapy study and Agent B cited an alcohol study, neither of which matched the 'Science Distorted' constraint). Since both agents failed to find the correct information requested by the specific constraints, it is a Low Quality Tie, despite Agent A having superior formatting.
GLM-4.7
Zhipu AI
DeepSeek V3.2
DeepSeek