Cover Image

Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yao, Michael S., Bastani, Osbert, Andersson, Alma, Biancalani, Tommaso, Bentaieb, Aïcha, Iriondo, Claudia
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
by: Yao, Michael S., et al.
Published: (2025)

Generative Adversarial Model-Based Optimization via Source Critic Regularization
by: Yao, Michael S., et al.
Published: (2024)

Conformal Constrained Policy Optimization for Cost-Effective LLM Agents
by: Si, Wenwen, et al.
Published: (2025)

Eurekaverse: Environment Curriculum Generation via Large Language Models
by: Liang, William, et al.
Published: (2024)

One-Shot Safety Alignment for Large Language Models via Optimal Dualization
by: Huang, Xinmeng, et al.
Published: (2024)

BrowserArena: Evaluating LLM Agents on Real-World Web Navigation Tasks
by: Anupam, Sagnik, et al.
Published: (2025)

Uncertainty in Language Models: Assessment through Rank-Calibration
by: Huang, Xinmeng, et al.
Published: (2024)

Asymptotic Normality of Generalized Low-Rank Matrix Sensing via Riemannian Geometry
by: Bastani, Osbert
Published: (2024)

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models
by: Uehara, Masatoshi, et al.
Published: (2024)

Counterfactual Generative Modeling with Variational Causal Inference
by: Wu, Yulun, et al.
Published: (2024)

DrEureka: Language Model Guided Sim-To-Real Transfer
by: Ma, Yecheng Jason, et al.
Published: (2024)

Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review
by: Uehara, Masatoshi, et al.
Published: (2024)

Hierarchically branched diffusion models leverage dataset structure for class-conditional generation
by: Tseng, Alex M., et al.
Published: (2022)

Eureka: Human-Level Reward Design via Coding Large Language Models
by: Ma, Yecheng Jason, et al.
Published: (2023)

Sharpness-Aware Black-Box Optimization
by: Ye, Feiyang, et al.
Published: (2024)

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
by: Tan, Rong-Xi, et al.
Published: (2025)

HYDRA: Model Factorization Framework for Black-Box LLM Personalization
by: Zhuang, Yuchen, et al.
Published: (2024)

In-Context Black-Box Optimization with Unreliable Feedback
by: Blumer, Nicolas Samuel, et al.
Published: (2026)

Jailbreaking Black Box Large Language Models in Twenty Queries
by: Chao, Patrick, et al.
Published: (2023)

Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
by: Miao, Ruiyao, et al.
Published: (2025)

Adding Conditional Control to Diffusion Models with Reinforcement Learning
by: Zhao, Yulai, et al.
Published: (2024)

Are AI Capabilities Increasing Exponentially? A Competing Hypothesis
by: Ge, Haosen, et al.
Published: (2026)

Beating the Winner's Curse via Inference-Aware Policy Optimization
by: Bastani, Hamsa, et al.
Published: (2025)

Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
by: Wang, Chenyu, et al.
Published: (2024)

OptunaHub: A Platform for Black-Box Optimization
by: Ozaki, Yoshihiko, et al.
Published: (2025)

Robust Guided Diffusion for Offline Black-Box Optimization
by: Chen, Can Sam, et al.
Published: (2024)

No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism
by: Li, Yubo, et al.
Published: (2025)

LiBOG: Lifelong Learning for Black-Box Optimizer Generation
by: Pei, Jiyuan, et al.
Published: (2025)

Dynamic Search for Inference-Time Alignment in Diffusion Models
by: Li, Xiner, et al.
Published: (2025)

Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning
by: Tsai, Yao-Hung Hubert, et al.
Published: (2024)

RAG-Enhanced Collaborative LLM Agents for Drug Discovery
by: Lee, Namkyeong, et al.
Published: (2025)

GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation
by: Galichin, Andrey V., et al.
Published: (2024)

Stochastic Online Conformal Prediction with Semi-Bandit Feedback
by: Ge, Haosen, et al.
Published: (2024)

Rethinking Algorithmic Fairness for Human-AI Collaboration
by: Ge, Haosen, et al.
Published: (2023)

A Fast, Reliable, and Secure Programming Language for LLM Agents with Code Actions
by: Mell, Stephen, et al.
Published: (2025)

ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
by: Meindl, Jamison, et al.
Published: (2025)

SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization
by: Meindl, Jamison, et al.
Published: (2025)

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
by: Hoang, Minh, et al.
Published: (2025)

Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties
by: Leguy, Jules, et al.
Published: (2021)

Position: Leverage Foundational Models for Black-Box Optimization
by: Song, Xingyou, et al.
Published: (2024)