mlsanityData to 7 Oct 2026

CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models

arXiv 2210.04191 ↗First posted 9 Oct 2022cs.CL cs.AI cs.LGcited by 7

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Abstract (arXiv)

We motivate and introduce CHARD: Clinical Health-Aware Reasoning across Dimensions, to investigate the capability of text generation models to act as implicit clinical knowledge bases and generate free-flow textual explanations about various health-related conditions across several dimensions. We collect and present an associated dataset, CHARDat, consisting of explanations about 52 health conditions across three clinical dimensions. We conduct extensive experiments using BART and T5 along with data augmentation, and perform automatic, human, and qualitative analyses. We show that while our models can perform decently, CHARD is very challenging with strong potential for further exploration.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 31 of its 45 references that are in the map. First posted on arXiv 9 Oct 2022.

Builds on

31 of 45 references.

References · 31

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19 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 2; 2026: 3.

7 papers.

  1. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  2. 2023Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationalescited by 33
  3. 2025Applications of Large Models in Medicinecited by 6
  4. 2025A Unified Definition of Hallucination: It's The World Model, Stupid!cited by 6
  5. 2026HalluWorld: A Controlled Benchmark for Hallucination via Reference World Modelscited by 2
  6. 2026To Memorize or to Retrieve: Scaling the Interaction Between Pretraining and Retrievalcited by 1
  7. 2026UniBuc at SemEval-2024 Task 2: Tailored Prompting with Solar for Clinical NLIcited by 0