activity
20182025
most citedLearning Context-Dependent Choice Functions

5 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2025

From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs

Jiawen Wang, Pritha Gupta, Ivan Habernal +3

Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-source LLMs are increasingly adopted in h…

stat.ML2024★ 1 cited

Information Leakage Detection through Approximate Bayes-optimal Prediction

Pritha Gupta, Marcel Wever, Eyke Hüllermeier

In today's data-driven world, the proliferation of publicly available information raises security concerns due to the information leakage (IL) problem. IL involves unintentionally…

cs.LG2022

Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets

David Schubert, Pritha Gupta, Marcel Wever

In anomaly detection, a prominent task is to induce a model to identify anomalies learned solely based on normal data. Generally, one is interested in finding an anomaly detector t…

cs.LG2019★ 5 cited

Learning Context-Dependent Choice Functions

Karlson Pfannschmidt, Pritha Gupta, Björn Haddenhorst +1

Choice functions accept a set of alternatives as input and produce a preferred subset of these alternatives as output. We study the problem of learning such functions under conditi…

stat.ML2018★ 4 cited

Deep Architectures for Learning Context-dependent Ranking Functions

Karlson Pfannschmidt, Pritha Gupta, Eyke Hüllermeier

Object ranking is an important problem in the realm of preference learning. On the basis of training data in the form of a set of rankings of objects, which are typically represent…