266 citations · 1.8k across the 115 of their papers we have counts for
148 papers
Regime Detection in Latent Factor Models -- A Bayesian Decision-Theoretic Approach
Karl Kristian Engelund
Regime-switching multi-factor models are widely used in quantitative finance, but filtering does not by itself determine when an agent should act on inferred regime changes. We for…
Are Multilingual LLMs Culturally-Diverse Reasoners? An Investigation into Multicultural Proverbs and Sayings
Chen Cecilia Liu, Fajri Koto, Timothy Baldwin +1
Large language models (LLMs) are highly adept at question answering and reasoning tasks, but when reasoning in a situational context, human expectations vary depending on the relev…
How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study
Andreas Waldis, Yufang Hou, Iryna Gurevych
The advent of pre-trained Language Models (LMs) has markedly advanced natural language processing, but their efficacy in out-of-distribution (OOD) scenarios remains a significant c…
CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and Calibration
Rachneet Sachdeva, Martin Tutek, Iryna Gurevych
In recent years, large language models (LLMs) have shown remarkable capabilities at scale, particularly at generating text conditioned on a prompt. In our work, we investigate the…
Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting
Tilman Beck, Hendrik Schuff, Anne Lauscher +1
Annotators' sociodemographic backgrounds (i.e., the individual compositions of their gender, age, educational background, etc.) have a strong impact on their decisions when working…
Are Emergent Abilities in Large Language Models just In-Context Learning?
Sheng Lu, Irina Bigoulaeva, Rachneet Sachdeva +2
Large language models, comprising billions of parameters and pre-trained on extensive web-scale corpora, have been claimed to acquire certain capabilities without having been speci…