EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems
Fuente:
arXiv
Saved in:
| Main Authors: | He, Yufei, Liu, Juncheng, Liu, Yue, Li, Yibo, Cao, Tri, Hu, Zhiyuan, Xu, Xinxing, Hooi, Bryan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EvoClinician: A Self-Evolving Agent for Multi-Turn Medical Diagnosis via Test-Time Evolutionary Learning
by: He, Yufei, et al.
Published: (2026)
by: He, Yufei, et al.
Published: (2026)
Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
by: Hu, Zhiyuan, et al.
Published: (2026)
by: Hu, Zhiyuan, et al.
Published: (2026)
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
by: Zhao, James Xu, et al.
Published: (2025)
by: Zhao, James Xu, et al.
Published: (2025)
Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance
by: He, Yufei, et al.
Published: (2025)
by: He, Yufei, et al.
Published: (2025)
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory
by: Wei, Tianxin, et al.
Published: (2025)
by: Wei, Tianxin, et al.
Published: (2025)
LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
by: Zheng, Tong, et al.
Published: (2026)
by: Zheng, Tong, et al.
Published: (2026)
Conversation for Non-verifiable Learning: Self-Evolving LLMs through Meta-Evaluation
by: Sui, Yuan, et al.
Published: (2026)
by: Sui, Yuan, et al.
Published: (2026)
Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates
by: Li, Yibo, et al.
Published: (2026)
by: Li, Yibo, et al.
Published: (2026)
Words or Vision: Do Vision-Language Models Have Blind Faith in Text?
by: Deng, Ailin, et al.
Published: (2025)
by: Deng, Ailin, et al.
Published: (2025)
Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study Over Open-ended Question Answering
by: Sui, Yuan, et al.
Published: (2024)
by: Sui, Yuan, et al.
Published: (2024)
MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research
by: Chen, Hui, et al.
Published: (2025)
by: Chen, Hui, et al.
Published: (2025)
Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
by: Lou, Zhanzhi, et al.
Published: (2026)
by: Lou, Zhanzhi, et al.
Published: (2026)
AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing
by: Li, Yuexin, et al.
Published: (2026)
by: Li, Yuexin, et al.
Published: (2026)
FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering
by: Sui, Yuan, et al.
Published: (2024)
by: Sui, Yuan, et al.
Published: (2024)
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
by: Hu, Zhiyuan, et al.
Published: (2025)
by: Hu, Zhiyuan, et al.
Published: (2025)
Enhancing Multi-Agent Debate System Performance via Confidence Expression
by: Lin, Zijie, et al.
Published: (2025)
by: Lin, Zijie, et al.
Published: (2025)
CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test
by: Hu, Zhangyi, et al.
Published: (2026)
by: Hu, Zhangyi, et al.
Published: (2026)
ConfTuner: Training Large Language Models to Express Their Confidence Verbally
by: Li, Yibo, et al.
Published: (2025)
by: Li, Yibo, et al.
Published: (2025)
KLong: Training LLM Agent for Extremely Long-horizon Tasks
by: Liu, Yue, et al.
Published: (2026)
by: Liu, Yue, et al.
Published: (2026)
ARTIS: Agentic Risk-Aware Test-Time Scaling via Iterative Simulation
by: Zeng, Xingshan, et al.
Published: (2026)
by: Zeng, Xingshan, et al.
Published: (2026)
State Tuning: State-based Test-Time Scaling on RWKV-7
by: Xiao, Liu, et al.
Published: (2025)
by: Xiao, Liu, et al.
Published: (2025)
Self-Improving LLM Agents at Test-Time
by: Acikgoz, Emre Can, et al.
Published: (2025)
by: Acikgoz, Emre Can, et al.
Published: (2025)
APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents
by: Li, Yibo, et al.
Published: (2026)
by: Li, Yibo, et al.
Published: (2026)
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
by: Xiong, Miao, et al.
Published: (2023)
by: Xiong, Miao, et al.
Published: (2023)
m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models
by: Huang, Xiaoke, et al.
Published: (2025)
by: Huang, Xiaoke, et al.
Published: (2025)
Adaptive Decoding via Test-Time Policy Learning for Self-Improving Generation
by: Bhardwaj, Asmita, et al.
Published: (2026)
by: Bhardwaj, Asmita, et al.
Published: (2026)
Automating Steering for Safe Multimodal Large Language Models
by: Wu, Lyucheng, et al.
Published: (2025)
by: Wu, Lyucheng, et al.
Published: (2025)
Agentic Test-Time Scaling for WebAgents
by: Lee, Nicholas, et al.
Published: (2026)
by: Lee, Nicholas, et al.
Published: (2026)
EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation
by: Guan, Xin, et al.
Published: (2026)
by: Guan, Xin, et al.
Published: (2026)
EvoMU: Evolutionary Machine Unlearning
by: Batorski, Pawel, et al.
Published: (2026)
by: Batorski, Pawel, et al.
Published: (2026)
Self-Harmony: Learning to Harmonize Self-Supervision and Self-Play in Test-Time Reinforcement Learning
by: Wang, Ru, et al.
Published: (2025)
by: Wang, Ru, et al.
Published: (2025)
EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
by: Guo, Qingyan, et al.
Published: (2023)
by: Guo, Qingyan, et al.
Published: (2023)
Rethinking Agentic Workflows: Evaluating Inference-Based Test-Time Scaling Strategies in Text2SQL Tasks
by: Guo, Jiajing, et al.
Published: (2025)
by: Guo, Jiajing, et al.
Published: (2025)
Guiding VLM Agents with Process Rewards at Inference Time for GUI Navigation
by: Hu, Zhiyuan, et al.
Published: (2025)
by: Hu, Zhiyuan, et al.
Published: (2025)
JudgeLRM: Large Reasoning Models as a Judge
by: Chen, Nuo, et al.
Published: (2025)
by: Chen, Nuo, et al.
Published: (2025)
TR-ICRL: Test-Time Rethinking for In-Context Reinforcement Learning
by: Jiang, Wenxuan, et al.
Published: (2026)
by: Jiang, Wenxuan, et al.
Published: (2026)
SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling
by: Chen, Jiefeng, et al.
Published: (2025)
by: Chen, Jiefeng, et al.
Published: (2025)
EvoPool: Evolutionary Programmatic Annotation for Label-Efficient Specialized Supervision
by: Xu, Tianyi, et al.
Published: (2026)
by: Xu, Tianyi, et al.
Published: (2026)
Evaluating the Paperclip Maximizer: Are RL-Based Language Models More Likely to Pursue Instrumental Goals?
by: He, Yufei, et al.
Published: (2025)
by: He, Yufei, et al.
Published: (2025)
C2-Evo: Co-Evolving Multimodal Data and Model for Self-Improving Reasoning
by: Chen, Xiuwei, et al.
Published: (2025)
by: Chen, Xiuwei, et al.
Published: (2025)
Similar Items
-
EvoClinician: A Self-Evolving Agent for Multi-Turn Medical Diagnosis via Test-Time Evolutionary Learning
by: He, Yufei, et al.
Published: (2026) -
Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
by: Hu, Zhiyuan, et al.
Published: (2026) -
Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
by: Zhao, James Xu, et al.
Published: (2025) -
Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance
by: He, Yufei, et al.
Published: (2025) -
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory
by: Wei, Tianxin, et al.
Published: (2025)