Information systems shape public discourse, decisions, and trust-yet we lack systematic ways to evaluate the accuracy of forward-looking statements (e.g., campaign promises, corporate forecasts). Media coverage is selective, standards are uneven, and the signal is buried in noise. The result: accountability gaps and eroded confidence.
IRAI brings IR and NLP communities together to design frameworks and tools that retrieve evidence, synthesize signals over time, and assess the fulfillment and reliability of claims and commitments. It complements ECIR's mission by tackling a pressing, real-world challenge with societal impact.
Why now? New multilingual datasets and shared tasks (e.g., corporate promise verification) make it timely to connect IR retrieval, aggregation, and evaluation with accountability questions at scale.
IRAI aspires to bridge NLP and IR, fostering shared benchmarks, methods, and open conversations.
Information systems shape public discourse, decisions, and trust-yet we lack systematic ways to evaluate the accuracy of forward-looking statements (e.g., campaign promises, corporate forecasts). Media coverage is selective, standards are uneven, and the signal is buried in noise. The result: accountability gaps and eroded confidence.
IRAI brings IR and NLP communities together to design frameworks and tools that retrieve evidence, synthesize signals over time, and assess the fulfillment and reliability of claims and commitments. It complements ECIR's mission by tackling a pressing, real-world challenge with societal impact.
Why now? New multilingual datasets and shared tasks (e.g., corporate promise verification) make it timely to connect IR retrieval, aggregation, and evaluation with accountability questions at scale.
What IRAI Aims to DoEvaluate the accuracy of forecasts and predictions by individuals, organizations, or systems.Assess fulfillment of commitments (political promises, corporate goals, public policies).Identify patterns of exaggeration or accountability gaps in public discourse.Promote transparency through evidence-based assessments and reproducible methodologies.IRAI aspires to bridge NLP and IR, fostering shared benchmarks, methods, and open conversations.
Website: https://nlpfin.github.io/sites/ECIR2026.html
H3SO3 ECIR2026 conference-secretariat@blueboxevents.nlTechnical Issues?
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