Hierarchical Textual Gradient Optimization for Automatic Prompt Optimization

Averkova Ekaterina, Kulin Nikita

Context-Aware Learning Curve Extrapolation with Prior-Data Fitted Networks

Cheng Yan, Steven Adriaensen, Tom Julian Viering

PAVO: Coupling-Aware Resource-Adaptive Routing for ASR → LLM → TTS Inference

NarasingaMoorthy VeiluKanthaPerumal, Mohammed Imthathullah

ScAn-Bench: Evaluating Scaling Analysis Methodology

Artin Sermaxhaj, Nastaran Alipour Gougeh, Donat Sinani, Johannes Hog, Neeratyoy Mallik, Steven Adriaensen, Jenia Jitsev, Danny Stoll

From Tables to Runtime: Predicting Algorithm Runtime Distributions with TabPFN

Hagverdi Ibrahimli, Katharina Eggensperger, Steven Adriaensen

Amortized Preferential Bayesian Optimization via Prior-Data Fitted Networks

Kseniia Kuvshinova, Steven Adriaensen, Sebastian Rojas Gonzalez, Raul Astudillo

Towards Benchmarking Agentic Data Scientists

Kartik Nagaraj Nayak, Nitishkumar Solpure, Niladri Mitra, Tom Zehle, Alexander Pfefferle, Omar Swelam, Frank Hutter

Poster-Only Papers

Amortized Multi-Objective Optimization Across Tasks with Generative Solution Modeling

Tingyang Wei, Jiao Liu, Abhishek Gupta, Chin Chun Ooi, Puay Siew Tan, Yew-Soon Ong

Learning to Solve and Optimize by Evolving Code

Veronika Semmelrock, Benedetta Strizzolo, Francesco Zuccato, Gerhard Friedrich, Patrick Rodler, Konstantin Schekotihin

Alpha Tester: Automated Discovery of Trading Strategies via LLM Multi-Agent AutoAI under Reliable, Bias-Free Evaluation

Hyungjin Ko

LISTEN to Your Preferences: An LLM Framework for Multi-Objective Selection

Adam S. Jovine, Tinghan Ye, Francis Bahk, Jingjing Wang, Matthew Ford, David B. Shmoys, Peter I. Frazier