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Agent Behavior Maps: Locating Agents by What They Would Do, Without Running Them

Paper recorded by Signals 4 on 2026-10-21 in cs.LG. 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.LG · 机器学习 · first seen 2026-10-22

Abstract

LLM agents with similar success rates can follow different action sequences. An Agent Behavior Map represents LLM-harness combinations using centered action log-likelihoods on shared reference trajectories, without requiring new environment rollouts from the target agent. We derive error bounds relating squared coordinate distances to trajectory KL under explicit assumptions, and across eight cros

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#218 most recent of 749 cs.LG papers we have recorded · ↑ newer: Code Comprehensor: Hierarchical Documentation and Cross-Modal Retrieva · ↓ older: Learning Adaptable Dexterous Skills via Hybrid Dexterous Mimicking
Cite this page: Agent Behavior Maps: Locating Agents by What They Would Do, Without Running Them: the #218 most recent of 749 cs.LG papers we have recorded (as of 2026-10-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/agent-behavior-maps-locating-agents-by-what-they-would-do-without-running-them.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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