15 papers
What Makes Linguistic Representations Good Models of High-Level Visual Perception in the Human Brain?
Anna Bavaresco, Ina KlariÄ, Raquel Fernández +1
Image descriptions represented with language models (LMs) predict human brain responses to naturalistic images in high-level visual regions, but the factors driving this predictivi…
ClimateCause: Complex and Implicit Causal Structures in Climate Reports
Liesbeth Allein, Nataly Pineda-Castañeda, Andrea Rocci +1
Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, direct causal relations. We in…
Assessing LLM Reasoning Through Implicit Causal Chain Discovery in Climate Discourse
Liesbeth Allein, Nataly Pineda-Castañeda, Andrea Rocci +1
How does a cause lead to an effect, and which intermediate causal steps explain their connection? This work scrutinizes the mechanistic causal reasoning capabilities of large langu…
Consistent Story Generation: Unlocking the Potential of Zigzag Sampling
Mingxiao Li, Mang Ning, Marie-Francine Moens
Text-to-image generation models have made significant progress in producing high-quality images from textual descriptions, yet they continue to struggle with maintaining subject co…
Automated Prompt Generation for Creative and Counterfactual Text-to-image Synthesis
Aleksa Jelaca, Ying Jiao, Chang Tian +1
Text-to-image generation has advanced rapidly with large-scale multimodal training, yet fine-grained controllability remains a critical challenge. Counterfactual controllability, d…
Structured Information for Improving Spatial Relationships in Text-to-Image Generation
Sander Schildermans, Chang Tian, Ying Jiao +1
Text-to-image (T2I) generation has advanced rapidly, yet faithfully capturing spatial relationships described in natural language prompts remains a major challenge. Prior efforts h…