4 citations · 5 across the 6 of their papers we have counts for
7 papers
Vision-Guided Iterative Refinement for Frontend Code Generation
Hannah Sansford, Derek H. C. Law, Wei Liu +3
Code generation with large language models often relies on multi-stage human-in-the-loop refinement, which is effective but very costly - particularly in domains such as frontend w…
Aligning Black-box Language Models with Human Judgments
Gerrit J. J. van den Burg, Gen Suzuki, Wei Liu +1
Large language models (LLMs) are increasingly used as automated judges to evaluate recommendation systems, search engines, and other subjective tasks, where relying on human evalua…
Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendation
Nithish Kannen, Yao Ma, Gerrit J. J. van den Burg +1
News recommendation is a challenging task that involves personalization based on the interaction history and preferences of each user. Recent works have leveraged the power of pret…
AI Assistants: A Framework for Semi-Automated Data Wrangling
Tomas Petricek, Gerrit J. J. van den Burg, Alfredo Nazábal +3
Data wrangling tasks such as obtaining and linking data from various sources, transforming data formats, and correcting erroneous records, can constitute up to 80% of typical data…
Wrangling Messy CSV Files by Detecting Row and Type Patterns
Gerrit J. J. van den Burg, Alfredo Nazabal, Charles Sutton
It is well known that data scientists spend the majority of their time on preparing data for analysis. One of the first steps in this preparation phase is to load the data from the…
Fast Meta-Learning for Adaptive Hierarchical Classifier Design
Gerrit J. J. van den Burg, Alfred O. Hero
We propose a new splitting criterion for a meta-learning approach to multiclass classifier design that adaptively merges the classes into a tree-structured hierarchy of increasingl…