30 citations · 47 across the 12 of their papers we have counts for
5 papers · 1 filter
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses
Xiao Ma, Swaroop Mishra, Ariel Liu +6
Large language model (LLM) powered chatbots are primarily text-based today, and impose a large interactional cognitive load, especially for exploratory or sensemaking tasks such as…
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning
Ananth Balashankar, Xiao Ma, Aradhana Sinha +4
As large language models (LLMs) are widely adopted, new safety issues and policies emerge, to which existing safety classifiers do not generalize well. If we have only observed a f…
Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting
Preethi Lahoti, Nicholas Blumm, Xiao Ma +8
A crucial challenge for generative large language models (LLMs) is diversity: when a user's prompt is under-specified, models may follow implicit assumptions while generating a res…
Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning
Xiao Ma, Swaroop Mishra, Ahmad Beirami +2
Language models still struggle on moral reasoning, despite their impressive performance in many other tasks. In particular, the Moral Scenarios task in MMLU (Multi-task Language Un…
A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures
Amanda Baughan, Allison Mercurio, Ariel Liu +3
Despite huge gains in performance in natural language understanding via large language models in recent years, voice assistants still often fail to meet user expectations. In this…