agent/papers/items/2026-2606-30259-multi-agentic-system-leveraging-open-source-llms-to-mitigate-disinformation-thre.md

Paper: Multi-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation Threats

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type: paper title: Multi-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation Threats authors: Sebastian Kula, Martin Tamajka year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.30259 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-29 updated_at: 2026-06-29 status: queued relevance: high topics:

• agent-evaluation
• multi-agent
• rag methods:

benchmarks:

models:

datasets:

• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 17 collection_queries: multi-agent-llm

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: multi-agent-llm
• inferred topics: agent-evaluation, multi-agent, rag
• arXiv categories: cs.CL
• collection score: 17

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.30259