Evidence map›Paper›PMID 42466065›Full record

ArticleFindings of ACL. ACL2026

Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine.

Sebastian Joseph, Lily Chen, Barry Wei, Michael Mackert, Iain J Marshall, Paul Pu Liang, Ramez Kouzy, Byron C Wallace, Junyi Jessy Li

Abstract read
In one paragraph

Article in Findings of ACL. ACL, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. FaithfulnessFindings of ACL. ACL · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sebastian JosephThe University of Texas at Austin.
Lily ChenStanford University.
Barry WeiIndiana University School of Medicine.
Michael MackertThe University of Texas at Austin.
Iain J MarshallKing's College London.
Paul Pu LiangMassachusetts Institute of Technology.
Ramez KouzyThe University of Texas MD Anderson Cancer Center.
Byron C WallaceNortheastern University.
Junyi Jessy LiThe University of Texas at Austin.

Funding

Building Safety Guards into LLMs for Trustworthy Automatic Simplification of Medical DocumentsR01LM014600 · NLM · UNIVERSITY OF TEXAS AT AUSTIN · PI Junyi Jessy Li, BYRON CASEY WALLACE · 2024 to 2026
$1.0M
NLM NIH HHS R01 LM014600Wellcome Trust
6 · The paper itself

Abstract

Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in adopting these systems for public health and medicine has grown due to the high-stakes nature of medical decisions and challenges in critically appraising a vast and diverse medical literature. Evidence-based medicine connects to every individual, and yet the nature of it is highly technical, rendering the medical literacy of majority users inadequate to sufficiently navigate the domain. Such problems with medical communication ripen the ground for end-to-end fact-checking agents: check a claim against current medical literature and return with an evidence-backed verdict. And yet, such systems remain largely unused. In this position paper, developed with expert input, we present the first study examining how clinical experts verify real claims from social media by synthesizing medical evidence. In searching for this upper-bound, we reveal fundamental challenges in end-to-end fact-checking when applied to medicine: Difficulties connecting claims in the wild to scientific evidence in the form of clinical trials; ambiguities in underspecified claims mixed with mismatched intentions; and inherently subjective veracity labels. We argue that fact-checking should be approached as an interactive communication problem, rather than an end-to-end process. Data and code are available at https://github.com/SebaJoe/decide-less-communicate-more.

Identifiers

PMID42466065
PMCPMC13373578

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.