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Environment Duels: A Microcosm of LLM Co-Evolution

Paper recorded by Signals 4 on 2026-10-21 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-21 on arXiv · recorded by Signals 4 on 2026-10-22

Category: cs.AI · 人工智能 · first seen 2026-10-22

Abstract

Through a tangle of real-world interactions, from synthetic training pipelines to data shared on the open web, frontier LLMs absorb what their predecessors and competitors create. How well does each model play its role in this ecosystem, as a creator and as a solver? We introduce Environment Duels, a dynamic agentic benchmark that evaluates both capabilities on interactive environments. Each model

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#203 most recent of 960 cs.AI papers we have recorded · ↑ newer: PhysiCalWorld: In-Context Physics Calibration for World Models · ↓ older: The End of Consensus Research?
Cite this page: Environment Duels: A Microcosm of LLM Co-Evolution: the #203 most recent of 960 cs.AI papers we have recorded (as of 2026-10-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/environment-duels-a-microcosm-of-llm-co-evolution.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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