Cover Image

Evolutionary Multi-Task Optimization for LLM-Guided Program Discovery

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gozeten, Halil Alperen, Zhang, Xuechen, Ildiz, Emrullah, Taga, Ege Onur, Javidi, Tara, Oymak, Samet
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to Correct: Calibrated Reinforcement Learning for Multi-Attempt Chain-of-Thought
by: Ildiz, Muhammed Emrullah, et al.
Published: (2026)

High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
by: Ildiz, M. Emrullah, et al.
Published: (2024)

TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
by: Taga, Ege Onur, et al.
Published: (2025)

Test-Time Training Provably Improves Transformers as In-context Learners
by: Gozeten, Halil Alperen, et al.
Published: (2025)

Continuous Chain of Thought Enables Parallel Exploration and Reasoning
by: Gozeten, Halil Alperen, et al.
Published: (2025)

Retrieval Augmented Time Series Forecasting
by: Tire, Kutay, et al.
Published: (2024)

Covariance-Aware Transformers for Quadratic Programming and Decision Making
by: Tire, Kutay, et al.
Published: (2026)

Learning to Bet for Horizon-Aware Anytime-Valid Testing
by: Taga, Ege Onur, et al.
Published: (2026)

Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
by: Zhang, Xuechen, et al.
Published: (2024)

From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
by: Ildiz, M. Emrullah, et al.
Published: (2024)

Mechanics of Next Token Prediction with Self-Attention
by: Li, Yingcong, et al.
Published: (2024)

Class-attribute Priors: Adapting Optimization to Heterogeneity and Fairness Objective
by: Zhang, Xuechen, et al.
Published: (2024)

On the Generalization Properties of Selective State-Space Models for Filtering Tasks for Unknown Systems
by: Tang, Alex, et al.
Published: (2026)

On the Power of Convolution Augmented Transformer
by: Li, Mingchen, et al.
Published: (2024)

VSPO: Vector-Steered Policy Optimization for Behavioral Control
by: Zhang, Xuechen, et al.
Published: (2026)

Latent Chain-of-Thought Improves Structured-Data Transformers
by: Dudley, Carson, et al.
Published: (2026)

Consequences of Kernel Regularity for Bandit Optimization
by: Lee, Madison, et al.
Published: (2025)

BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning
by: Zhang, Xuechen, et al.
Published: (2025)

Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement
by: Zhang, Xuechen, et al.
Published: (2025)

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
by: Zhang, Xuechen, et al.
Published: (2025)

Selective Attention: Enhancing Transformer through Principled Context Control
by: Zhang, Xuechen, et al.
Published: (2024)

Learning to Ask: Decision Transformers for Adaptive Quantitative Group Testing
by: Soleymani, Mahdi, et al.
Published: (2025)

Universal Lower Bounds and Optimal Rates: Achieving Minimax Clustering Error in Sub-Exponential Mixture Models
by: Dreveton, Maximilien, et al.
Published: (2024)

Coverage Analysis for Digital Cousin Selection -- Improving Multi-Environment Q-Learning
by: Bozkus, Talha, et al.
Published: (2024)

From Relative Entropy to Minimax: A Unified Framework for Coverage in MDPs
by: Gu, Xihe, et al.
Published: (2026)

$κ$-Explorer: A Unified Framework for Active Model Estimation in MDPs
by: Gu, Xihe, et al.
Published: (2026)

In-Context Learning Under Regime Change
by: Dudley, Carson, et al.
Published: (2026)

Attention with Trained Embeddings Provably Selects Important Tokens
by: Wu, Diyuan, et al.
Published: (2025)

Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
by: Li, Yingcong, et al.
Published: (2024)

Convex and Non-convex Federated Learning with Stale Stochastic Gradients: Diminishing Step Size is All You Need
by: Zheng, Xinran, et al.
Published: (2026)

Can Transformers Learn Optimal Filtering for Unknown Systems?
by: Balim, Haldun, et al.
Published: (2023)

Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
by: Park, Jongho, et al.
Published: (2024)

CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
by: Ahmed, Sk Miraj, et al.
Published: (2024)

Transformers as Support Vector Machines
by: Tarzanagh, Davoud Ataee, et al.
Published: (2023)

Localized Distributional Robustness in Submodular Multi-Task Subset Selection
by: Kaya, Ege C., et al.
Published: (2024)

Trojan Cleansing with Neural Collapse
by: Gu, Xihe, et al.
Published: (2024)

Multi-Task Equation Discovery
by: Bee, S C, et al.
Published: (2025)

Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate
by: Liu, Hugh Xuechen, et al.
Published: (2026)

CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning
by: Javadi, Amirhosein, et al.
Published: (2026)

Primal Dual Continual Learning: Balancing Stability and Plasticity through Adaptive Memory Allocation
by: Elenter, Juan, et al.
Published: (2023)