1 citations · 2 across the 17 of their papers we have counts for
4 papers · 2 filters
Do Language Models Update their Forecasts with New Information?
Zhangdie Yuan, Zifeng Ding, Andreas Vlachos
Prior work has largely treated future event prediction as a static task, failing to consider how forecasts should evolve as new evidence emerges. To address this gap, we introduce…
Social Good or Scientific Curiosity? Uncovering the Research Framing Behind NLP Artefacts
Eric Chamoun, Nedjma Ousidhoum, Michael Schlichtkrull +1
Clarifying the research framing of NLP artefacts (e.g., models, datasets, etc.) is crucial to aligning research with practical applications. Recent studies manually analyzed NLP re…
AVerImaTeC: A Dataset for Automatic Verification of Image-Text Claims with Evidence from the Web
Rui Cao, Zifeng Ding, Zhijiang Guo +2
Textual claims are often accompanied by images to enhance their credibility and spread on social media, but this also raises concerns about the spread of misinformation. Existing d…
Capturing Symmetry and Antisymmetry in Language Models through Symmetry-Aware Training Objectives
Zhangdie Yuan, Andreas Vlachos
Capturing symmetric (e.g., country borders another country) and antisymmetric (e.g., parent_of) relations is crucial for a variety of applications. This paper tackles this challeng…