Gianluca Demartini

Large Language Models as Assessors: On the Impact of Relevance Scales featured image

Large Language Models as Assessors: On the Impact of Relevance Scales

Poster - The 48th European Conference on Information Retrieval (ECIR 2026). Delft, The Netherlands.

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Large Language Models as Assessors: On the Impact of Relevance Scales

Traditionally, relevance judgments have relied on human annotators, but recent advances in Large Language Models (LLMs) have prompted growing interest in their use as a proxy for …

riccardo-zamolo

Longitudinal Loyalty: Understanding The Barriers To Running Longitudinal Studies On Crowdsourcing Platforms

Crowdsourcing tasks have been widely used to collect a large number of human labels at scale. While some of these tasks are deployed by requesters and performed only once by crowd …

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Michael Soprano

Crowdsourced Fact-checking: Does It Actually Work?

There is an important ongoing effort aimed to tackle misinformation and to perform reliable fact-checking by employing human assessors at scale, with a crowdsourcing-based …

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Cognitive Biases in Fact-Checking and Their Countermeasures: A Review

The increase of the amount of misinformation spread every day online is a huge threat to the society. Organizations and researchers are working to contrast this misinformation …

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Michael Soprano

How Many Crowd Workers Do I Need? On Statistical Power When Crowdsourcing Relevance Judgments

To scale the size of Information Retrieval collections, crowdsourcing has become a common way to collect relevance judgments at scale. Crowdsourcing experiments usually employ …

kevin-roitero

A Neural Model to Jointly Predict and Explain Truthfulness of Statements

Automated fact-checking (AFC) systems exist to combat disinformation, however their complexity usually makes them opaque to the end user, making it difficult to foster trust in the …

erik-brand

E-BART: Jointly Predicting and Explaining Truthfulness

Automated fact-checking (AFC) systems exist to combat disinformation, however their complexity makes them opaque to the end user, making it difficult to foster trust. In this …

erik-brand

Can The Crowd Judge Truthfulness? A Longitudinal Study on Recent Misinformation About COVID-19

Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd …

kevin-roitero

The COVID-19 Infodemic: Can the Crowd Judge Recent Misinformation Objectively?

Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large. Very recently, the problem has …

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