Sonia Laguna
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    • Models Designed to Forget: Machine Unlearning via Key Deletion
    • Cartridges++: KV Cache Compression without Off-Context Derailment
    • ConRAG: Lightweight Inference of Multi-Hop Relations
    • Cyclostationary Phase Conditioning for Medical Time Series Diffusion
    • KV-Kaizen: Learning Context-Adaptive Cache Compression Choices
    • DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures
    • Reference-Guided Machine Unlearning
    • Structure is Supervision: Multiview Masked Autoencoders for Radiology
    • Foundation Model for Cardiac Time Series via Masked Latent Attention
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    • Steering Generative Models for Accessibility: EasyRead Image Generation
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    • Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes
    • Measuring Leakage in Concept-Based Methods: An Information Theoretic Approach
    • Text To 3D Object Generation For Scalable Room Assembly
    • Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings
    • Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks
    • RadVLM: A Multitask Conversational Vision-Language Model for Radiology
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    • ExpLIMEable: An exploratory framework for LIME
    • Super-resolution of portable low-field MRI in real scenarios: integration with denoising and domain adaptation
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    • 📝 MUNKEY (Machine Unlearning) got accepted at NeurIPS 2026🇦🇺!
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    • 📝 New paper on multimodal representation learning accepted to TMLR and on generative models for accessibility at CHI 2026
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    • 📝 Summer research update! Four first author publications have been accepted and will be presented this summer at ICML, MLHC and IPCAI
    • 📝 Attending ICLR 2025 in Singapore, our four workshop papers got accepted with an oral (Best Paper Award 🏆) contribution!
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    • 🗣️ Our Workshop on GenAI meets XAI was accepted!
    • 📝 Our two main conference papers on Concept Bottleneck Models got accepted at NeurIPS 2024!
    • 📝 Our two workshop papers got accepted at NeurIPS 2024!
    • 🖥️ Joined Google as a Research Intern and later extended as a Student Researcher.
    • 📝 Our main conference paper on Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders got accepted at ICLR 2024!
    • 📝 Our workshop paper got accepted at NeurIPS 2023.
    • 🗣️ Our Workshop on Deep Generative Models for Health was accepted!
    • 🏅 Featured in the Nova List top talents in Spain!
    • 📚 Attended the Machine Learning Summer School (MLSS) in South Africa!
    • 🏛️ Started my PhD in Machine Learning at ETH Zurich.
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    • 🏛️ Selected as Amgen Scholar to do research at ETH Zurich!
    • 🏛️ Started an exchange year at Georgia Institute of Technology!
    • 🏛️ Started my BSc in Biomedical Engineering at Universidad Carloss III de Madrid!
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DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures

Aug 20, 2026·
Eleonora Gualdoni
Sonia Laguna
Sonia Laguna
,
Louis Béthune
,
Joao Monteiro
,
Pierre Ablin
,
Marco Cuturi
· 0 min read
PDF
Type
Conference paper
Publication
Preprint - Arxiv
Last updated on Aug 20, 2026
Sonia Laguna
Authors
Sonia Laguna
Research @Apple MLR
PhD in Machine Learning @ETH Zurich
← KV-Kaizen: Learning Context-Adaptive Cache Compression Choices Sep 25, 2026
Reference-Guided Machine Unlearning Mar 14, 2026 →

© 2026 Sonia Laguna. This work is licensed under CC BY NC ND 4.0

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