2 citations · 6 across the 8 of their papers we have counts for
8 papers
Beyond Task Completion: Revealing Corrupt Success in LLM Agents through Procedure-Aware Evaluation
Hongliu Cao, Ilias Driouich, Eoin Thomas
Large Language Model (LLM)-based agents are increasingly adopted in high-stakes settings, but current benchmarks evaluate mainly whether a task was completed, not how. We introduce…
When LLMs Imagine People: A Human-Centered Persona Brainstorm Audit for Bias and Fairness in Creative Applications
Hongliu Cao, Eoin Thomas, Rodrigo Acuna Agost
Large Language Models (LLMs) used in creative workflows can reinforce stereotypes and perpetuate inequities, making fairness auditing essential. Existing methods rely on constraine…
Diverse And Private Synthetic Datasets Generation for RAG evaluation: A multi-agent framework
Ilias Driouich, Hongliu Cao, Eoin Thomas
Retrieval-augmented generation (RAG) systems improve large language model outputs by incorporating external knowledge, enabling more informed and context-aware responses. However,…
Multi-Agent LLM Judge: automatic personalized LLM judge design for evaluating natural language generation applications
Hongliu Cao, Ilias Driouich, Robin Singh +1
Large Language Models (LLMs) have demonstrated impressive performance across diverse domains, yet they still encounter challenges such as insufficient domain-specific knowledge, bi…
Inclusive normalization of face images to passport format
Hongliu Cao, Minh Nhat Do, Alexis Ravanel +1
Face recognition has been used more and more in real world applications in recent years. However, when the skin color bias is coupled with intra-personal variations like harsh illu…
Multi-view user representation learning for user matching without personal information
Hongliu Cao, Ilias El Baamrani, Eoin Thomas
As the digitization of travel industry accelerates, analyzing and understanding travelers' behaviors becomes increasingly important. However, traveler data frequently exhibit high…
Local Model Reconstruction Attacks in Federated Learning and their Uses
Ilias Driouich, Chuan Xu, Giovanni Neglia +2
In this paper, we initiate the study of local model reconstruction attacks for federated learning, where a honest-but-curious adversary eavesdrops the messages exchanged between a…
Destination similarity based on implicit user interest
Hongliu Cao, Eoin Thomas
With the digitization of travel industry, it is more and more important to understand users from their online behaviors. However, online travel industry data are more challenging t…