49 citations · 101 across the 20 of their papers we have counts for
20 papers
The Magic Correlations: Understanding Knowledge Transfer from Pretraining to Supervised Fine-Tuning
Simin Fan, Dimitris Paparas, Natasha Noy +3
Understanding how language model capabilities transfer from pretraining to supervised fine-tuning (SFT) is fundamental to efficient model development and data curation. In this wor…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings
Pura Peetathawatchai, Wei-Ning Chen, Berivan Isik +2
Personalizing large-scale diffusion models poses serious privacy risks, especially when adapting to small, sensitive datasets. A common approach is to fine-tune the model using dif…
Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs
Ashwinee Panda, Berivan Isik, Xiangyu Qi +3
Existing methods for adapting large language models (LLMs) to new tasks are not suited to multi-task adaptation because they modify all the model weights -- causing destructive int…
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai +10
Maximum Manifold Capacity Representations (MMCR) is a recent multi-view self-supervised learning (MVSSL) method that matches or surpasses other leading MVSSL methods. MMCR is intri…
Improved Communication-Privacy Trade-offs in Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen, Berivan Isik, Peter Kairouz +3
We study mean estimation under central differential privacy and communication constraints, and address two key challenges: firstly, existing mean estimation schemes that simu…