12 papers
Psychological Steering in LLMs: An Evaluation of Effectiveness and Trustworthiness
Amin Banayeeanzade, Ala N. Tak, Fatemeh Bahrani +5
The ability to control LLMs' emulated emotional states and personality traits is an essential step in enabling rich, human-centered interactions in socially interactive settings. W…
ContextLeak: Auditing Leakage in Private In-Context Learning Methods
Jacob Choi, Shuying Cao, Xingjian Dong +4
In-Context Learning (ICL) has become a standard technique for adapting Large Language Models (LLMs) to specialized tasks by supplying task-specific exemplars within the prompt. How…
Beyond URLs: Metadata Diversity and Position for Efficient LLM Pretraining
Dongyang Fan, Diba Hashemi, Sai Praneeth Karimireddy +1
Incorporating metadata in Large Language Models (LLMs) pretraining has recently emerged as a promising approach to accelerate training. However prior work highlighted only one usef…
f-INE: A Hypothesis Testing Framework for Estimating Influence under Training Randomness
Subhodip Panda, Dhruv Tarsadiya, Shashwat Sourav +2
Influence estimation methods promise to explain and debug machine learning by estimating the impact of individual samples on the final model. Yet, existing methods collapse under t…
A Closer Look at Personalized Fine-Tuning in Heterogeneous Federated Learning
Minghui Chen, Hrad Ghoukasian, Ruinan Jin +3
Federated Learning (FL) enables decentralized, privacy-preserving model training but struggles to balance global generalization and local personalization due to non-identical data…
Optimization with Access to Auxiliary Information
El Mahdi Chayti, Sai Praneeth Karimireddy
We investigate the fundamental optimization question of minimizing a target function , whose gradients are expensive to compute or have limited availability, given access to som…