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References (12)

[1]
GAP: Graph-Based Agent Planning with Parallel Tool Use and Reinforcement Learning
2025Jiaqi Wu, Qinlao Zhao et al.
[2]
ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution
2025R. Lange, Yuki Imajuku et al.
[3]
AlphaEvolve: A coding agent for scientific and algorithmic discovery
2025Alexander Novikov, Ngân V˜u et al.
[4]
RouteLLM: Learning to Route LLMs with Preference Data
2024Isaac Ong, Amjad Almahairi et al.
[5]
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
2024Naman Jain, King Han et al.
[6]
Can LLMs Learn Uncertainty on Their Own? Expressing Uncertainty Effectively in A Self-Training Manner
2024Shudong Liu, Zhao Li et al.
[7]
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
2023Lingjiao Chen, M. Zaharia et al.
[8]
Speculative Decoding with Big Little Decoder
2023Sehoon Kim, K. Mangalam et al.
[9]
Program Synthesis with Large Language Models
2021Jacob Austin, Augustus Odena et al.
[10]
River: machine learning for streaming data in Python
2020Jacob Montiel, Max Halford et al.
[11]
Illuminating search spaces by mapping elites
2015Jean-Baptiste Mouret, J. Clune
[12]
Adaptive Learning from Evolving Data Streams
2009A. Bifet, Ricard Gavaldà

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