7 papers · 1 filter
MEDAKA: Construction of Biomedical Knowledge Graphs Using Large Language Models
Asmita Sengupta, David Antony Selby, Sebastian Josef Vollmer +1
Knowledge graphs (KGs) are increasingly used to represent biomedical information in structured, interpretable formats. However, existing biomedical KGs often focus narrowly on mole…
Decomposing Visual Classification: Assessing Tree-Based Reasoning in VLMs
Sary Elmansoury, Islam Mesabah, Gerrit Großmann +4
Vision language models (VLMs) excel at zero-shot visual classification, but their performance on fine-grained tasks and large hierarchical label spaces is understudied. This paper…
BioDisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation
Yujing Ke, Kevin George, Kathan Pandya +5
Identifying novel hypotheses is essential to scientific research, yet this process risks being overwhelmed by the sheer volume and complexity of available information. Existing aut…
The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete
Gerrit Großmann, Larisa Ivanova, Sai Leela Poduru +4
According to Yuval Noah Harari, large-scale human cooperation is driven by shared narratives that encode common beliefs and values. This study explores whether such narratives can…
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity
Yahya Aalaila, Gerrit Großmann, Sumantrak Mukherjee +2
Counterfactual reasoning, a cornerstone of human cognition and decision-making, is often seen as the 'holy grail' of causal learning, with applications ranging from interpreting ma…
Neural Spatiotemporal Point Processes: Trends and Challenges
Sumantrak Mukherjee, Mouad Elhamdi, George Mohler +4
Spatiotemporal point processes (STPPs) are probabilistic models for events occurring in continuous space and time. Real-world event data often exhibit intricate dependencies and he…
CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning
Yousef Koka, David Selby, Gerrit Großmann +2
Data preprocessing is often paid little attention in machine learning, despite its potentially significant impact on model performance. While automated machine learning pipelines a…