2 citations · 4 across the 15 of their papers we have counts for
5 papers · 1 filter
Towards Effective Discrimination Testing for Generative AI
Thomas P. Zollo, Nikita Rajaneesh, Richard Zemel +2
Generative AI (GenAI) models present new challenges in regulating against discriminatory behavior. In this paper, we argue that GenAI fairness research still has not met these chal…
Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification
Tao Meng, Ninareh Mehrabi, Palash Goyal +6
We propose a constraint learning schema for fine-tuning Large Language Models (LLMs) with attribute control. Given a training corpus and control criteria formulated as a sequence-l…
Improving Predictor Reliability with Selective Recalibration
Thomas P. Zollo, Zhun Deng, Jake C. Snell +2
A reliable deep learning system should be able to accurately express its confidence with respect to its predictions, a quality known as calibration. One of the most effective ways…
Toward Informal Language Processing: Knowledge of Slang in Large Language Models
Zhewei Sun, Qian Hu, Rahul Gupta +2
Recent advancement in large language models (LLMs) has offered a strong potential for natural language systems to process informal language. A representative form of informal langu…
Partial Federated Learning
Tiantian Feng, Anil Ramakrishna, Jimit Majmudar +6
Federated Learning (FL) is a popular algorithm to train machine learning models on user data constrained to edge devices (for example, mobile phones) due to privacy concerns. Typic…