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Main Authors: Xian, R. Patrick, Cui, Qiming, Bauer, Stefan, Abbasi-Asl, Reza
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.04188
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author Xian, R. Patrick
Cui, Qiming
Bauer, Stefan
Abbasi-Asl, Reza
author_facet Xian, R. Patrick
Cui, Qiming
Bauer, Stefan
Abbasi-Asl, Reza
contents Temporal progression is an integral part of knowledge accumulation and update. Web search is frequently adopted as grounding for agent knowledge, yet an improper configuration affects the quality of the agent's responses. Here, we assess the agent behavior using distinct date-controlled tools (DCTs) as stress test to measure the knowledge variability of large language model (LLM) agents. We demonstrate the temporal effects of an LLM agent as a writing assistant, which uses web search to complete scientific publication abstracts. We show that the temporality of search engine translates into tool-dependent agent performance but can be alleviated with base model choice and explicit reasoning instructions such as chain-of-thought prompting. Our results indicate that agent design and evaluations should take a dynamical view and implement measures to account for the temporal influence of external resources to ensure reliability.
format Preprint
id arxiv_https___arxiv_org_abs_2503_04188
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Measuring temporal effects of agent knowledge by date-controlled tool use
Xian, R. Patrick
Cui, Qiming
Bauer, Stefan
Abbasi-Asl, Reza
Computation and Language
Information Retrieval
Temporal progression is an integral part of knowledge accumulation and update. Web search is frequently adopted as grounding for agent knowledge, yet an improper configuration affects the quality of the agent's responses. Here, we assess the agent behavior using distinct date-controlled tools (DCTs) as stress test to measure the knowledge variability of large language model (LLM) agents. We demonstrate the temporal effects of an LLM agent as a writing assistant, which uses web search to complete scientific publication abstracts. We show that the temporality of search engine translates into tool-dependent agent performance but can be alleviated with base model choice and explicit reasoning instructions such as chain-of-thought prompting. Our results indicate that agent design and evaluations should take a dynamical view and implement measures to account for the temporal influence of external resources to ensure reliability.
title Measuring temporal effects of agent knowledge by date-controlled tool use
topic Computation and Language
Information Retrieval
url https://arxiv.org/abs/2503.04188