Copertina

RedAHD: Reduction-Based End-to-End Automatic Heuristic Design with Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Thach, Nguyen, Riahifar, Aida, Huynh, Nathan, Chan, Hau
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Large Language Models for Designing Participatory Budgeting Rules
di: Thach, Nguyen, et al.
Pubblicazione: (2026)

Large Language Models for Multi-Facility Location Mechanism Design
di: Thach, Nguyen, et al.
Pubblicazione: (2025)

End-to-End Ontology Learning with Large Language Models
di: Lo, Andy, et al.
Pubblicazione: (2024)

Exploring the Feasibility of End-to-End Large Language Model as a Compiler
di: Zhang, Hongbin, et al.
Pubblicazione: (2025)

An End-to-End Framework for Building Large Language Models for Software Operations
di: He, Jingkai, et al.
Pubblicazione: (2026)

AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design
di: Lv, Haoze, et al.
Pubblicazione: (2026)

End-to-End Personalization: Unifying Recommender Systems with Large Language Models
di: Ebrat, Danial, et al.
Pubblicazione: (2025)

LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models
di: Mozaffari, Mohammad, et al.
Pubblicazione: (2026)

End-to-end Planner Training for Language Modeling
di: Cornille, Nathan, et al.
Pubblicazione: (2024)

Towards End-to-End Network Intent Management with Large Language Models
di: Dinh, Lam, et al.
Pubblicazione: (2025)

An End-to-End Depth-Based Pipeline for Selfie Image Rectification
di: Alhawwary, Ahmed, et al.
Pubblicazione: (2024)

Continual Learning for Monolingual End-to-End Automatic Speech Recognition
di: Eeckt, Steven Vander, et al.
Pubblicazione: (2021)

Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting
di: Luo, Miaosen, et al.
Pubblicazione: (2025)

End-to-End Compression for Tabular Foundation Models
di: Zabërgja, Guri, et al.
Pubblicazione: (2026)

RANDPOL: Parameter-Efficient End-to-End Quadruped Locomotion via Randomized Policy Learning
di: Liu, Zhuochen, et al.
Pubblicazione: (2025)

AnyBipe: An End-to-End Framework for Training and Deploying Bipedal Robots Guided by Large Language Models
di: Yao, Yifei, et al.
Pubblicazione: (2024)

Dynamic Chunking for End-to-End Hierarchical Sequence Modeling
di: Hwang, Sukjun, et al.
Pubblicazione: (2025)

A Novel GAN Approach to Augment Limited Tabular Data for Short-Term Substance Use Prediction
di: Thach, Nguyen, et al.
Pubblicazione: (2024)

ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
di: Liang, Jiacheng, et al.
Pubblicazione: (2026)

AudioJailbreak: Jailbreak Attacks against End-to-End Large Audio-Language Models
di: Chen, Guangke, et al.
Pubblicazione: (2025)

GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
di: Kim, Jinuk, et al.
Pubblicazione: (2025)

Bridging the Divide: End-to-End Sequence-Graph Learning
di: Chen, Yuen, et al.
Pubblicazione: (2025)

An End-to-End Approach for Child Reading Assessment in the Xhosa Language
di: Chevtchenko, Sergio, et al.
Pubblicazione: (2025)

Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin
di: Rufai, Amina Mardiyyah, et al.
Pubblicazione: (2020)

Efficient Frequency Selective Surface Analysis via End-to-End Model-Based Learning
di: Hammami, Cheima, et al.
Pubblicazione: (2024)

An End-to-End Model for Time Series Classification In the Presence of Missing Values
di: Yao, Pengshuai, et al.
Pubblicazione: (2024)

End-to-End Optimal Detector Design with Mutual Information Surrogates
di: Wozniak, Kinga Anna, et al.
Pubblicazione: (2025)

Automatic Prompt Selection for Large Language Models
di: Do, Viet-Tung, et al.
Pubblicazione: (2024)

Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model
di: Ni, Bo, et al.
Pubblicazione: (2025)

Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learning
di: Huebotter, Justus, et al.
Pubblicazione: (2025)

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
di: You, Junwei, et al.
Pubblicazione: (2024)

Time-Varying Audio Effect Modeling by End-to-End Adversarial Training
di: Bourdin, Yann, et al.
Pubblicazione: (2025)

Co-Designing Binarized Transformer and Hardware Accelerator for Efficient End-to-End Edge Deployment
di: Ji, Yuhao, et al.
Pubblicazione: (2024)

FLAME-MoE: A Transparent End-to-End Research Platform for Mixture-of-Experts Language Models
di: Kang, Hao, et al.
Pubblicazione: (2025)

Beyond the Node: Clade-level Selection for Efficient MCTS in Automatic Heuristic Design
di: Lai, Kezhao, et al.
Pubblicazione: (2026)

VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision
di: Xu, Yi, et al.
Pubblicazione: (2024)

Robust Explainer Recommendation for Time Series Classification
di: Nguyen, Thu Trang, et al.
Pubblicazione: (2023)

Privacy-Preserving End-to-End Spoken Language Understanding
di: Wang, Yinggui, et al.
Pubblicazione: (2024)

E2ESlack: An End-to-End Graph-Based Framework for Pre-Routing Slack Prediction
di: Bodhe, Saurabh, et al.
Pubblicazione: (2025)

End-to-End Test-Time Training for Long Context
di: Tandon, Arnuv, et al.
Pubblicazione: (2025)