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Long-Horizon Agent Trajectory Attribution: A Unified Benchmark and Fine-Grained Annotation Framework
agentsobservabilitysafetybenchmarking
2608.06909
Builder Relevance
Aug 787%
Abstract
This paper frames trajectory attribution as identifying which components of a multi-step agent execution contributed to a target behavior.
Reality Card
Core Claim
Agent observability should attribute outcomes to instructions, observations, tool interactions, memory, and intermediate actions rather than inspecting only a final answer.
Method / Result
The paper reports more than 1,300 annotated trajectories and a reusable protocol for model-adaptive trajectory annotation and evaluation.
Limitations
The benchmark focuses on attribution annotations and evaluation structure; teams must still test whether it matches their own agent framework, logging fidelity, and risk model.
Paper to code
Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.
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