5 papers · 1 filter
STAMP: Selective Task-Aware Mechanism for Text Privacy
Fengwei Tian, Payel Bhattacharjee, Heidi Hanson +3
We present STAMP (Selective Task-Aware Mechanism for Text Privacy), a new framework for task-aware text privatization that achieves an improved privacy-utility trade-off. STAMP sel…
MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling
Payel Bhattacharjee, Osvaldo Simeone, Ravi Tandon
Reward modeling is central to RLHF, RLAIF, and PPO-based alignment, but its reliability is often limited by scarce and heterogeneous human preference data. In this paper, we introd…
Conformal Sparsification for Bandwidth-Efficient Edge-Cloud Speculative Decoding
Payel Bhattacharjee, Fengwei Tian, Meiyu Zhong +3
Edge-cloud speculative decoding (SD) accelerates inference by having a cloud-based large language model (LLM) that verifies draft tokens generated by a resource-constrained small l…
PROPS: Progressively Private Self-alignment of Large Language Models
Noel Teku, Fengwei Tian, Payel Bhattacharjee +3
Alignment is a key step in developing Large Language Models (LLMs) using human feedback to ensure adherence to human values and societal norms. Dependence on human feedback raises…
Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Data
Zihan Guan, Zhiyuan Zhao, Fengwei Tian +5
Epidemic analyses increasingly rely on heterogeneous datasets, many of which are sensitive and require strong privacy protection. Although differential privacy (DP) has become a st…