π backfill:2025-10-15..2025-10-15 Β· Terminal β 1 paper(s)
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1. EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems
Authors: Yufei He, Juncheng Liu, Yue Liu, Yibo Li, Tri Cao, et al.
Venue: arXiv 2025/10 | benchmark
The paper introduces the Jericho Test-Time Learning (J-TTL) benchmark to evaluate how agents improve performance across consecutive episodes in text-based CLI environments. It proposes EvoTest, an evolutionary framework that uses an Evolver Agent to iteratively refine an Actor Agent's prompts and memory based on game transcripts.
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/approve all β accept all papers/approve 1,3 β accept papers 1 and 3/reject 2 β discard paper 2/approve 1,3 /reject 2 β mixed/edit 1 category=code_generation β change category before approving/edit 1 venue=ICSE 2026 β fix venue
π backfill:2025-10-15..2025-10-15 Β· Terminal β 1 paper(s)
1. EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems
Authors: Yufei He, Juncheng Liu, Yue Liu, Yibo Li, Tri Cao, et al.
Venue: arXiv 2025/10 |
benchmarkReview commands (comment on this issue):
/approve allβ accept all papers/approve 1,3β accept papers 1 and 3/reject 2β discard paper 2/approve 1,3 /reject 2β mixed/edit 1 category=code_generationβ change category before approving/edit 1 venue=ICSE 2026β fix venue