6 citations · 11 across the 7 of their papers we have counts for
8 papers
Algorithmic Harms Associated with Generative Model-Augmented Recommendation Systems
Christine Herlihy, Xumei Xi, Shloka Desai +2
In this work, we consider algorithmic harms that may arise as generative models are incorporated into machine learning platforms. We argue that existing harm taxonomies and threat…
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots
Christine Herlihy, Jennifer Neville, Tobias Schnabel +1
We explore the use of Large Language Model (LLM-based) chatbots to power recommender systems. We observe that the chatbots respond poorly when they encounter under-specified reques…
A structured regression approach for evaluating model performance across intersectional subgroups
Christine Herlihy, Kimberly Truong, Alexandra Chouldechova +1
Disaggregated evaluation is a central task in AI fairness assessment, where the goal is to measure an AI system's performance across different subgroups defined by combinations of…
Data Contamination Through the Lens of Time
Manley Roberts, Himanshu Thakur, Christine Herlihy +2
Recent claims about the impressive abilities of large language models (LLMs) are often supported by evaluating publicly available benchmarks. Since LLMs train on wide swaths of the…
Networked Restless Bandits with Positive Externalities
Christine Herlihy, John P. Dickerson
Restless multi-armed bandits are often used to model budget-constrained resource allocation tasks where receipt of the resource is associated with an increased probability of a fav…
MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain
Christine Herlihy, Rachel Rudinger
Crowdworker-constructed natural language inference (NLI) datasets have been found to contain statistical artifacts associated with the annotation process that allow hypothesis-only…
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting
Christine Herlihy, Aviva Prins, Aravind Srinivasan +1
Restless and collapsing bandits are often used to model budget-constrained resource allocation in settings where arms have action-dependent transition probabilities, such as the al…
A Compositional Framework for Scientific Model Augmentation
Micah Halter, Christine Herlihy, James Fairbanks
Scientists construct and analyze computational models to understand the world. That understanding comes from efforts to augment, combine, and compare models of related phenomena. W…