agent/papers/items/2026-2603-02711-a-natural-language-agentic-approach-to-study-affective-polarization.md

Paper: A Natural Language Agentic Approach to Study Affective Polarization

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type: paper title: A Natural Language Agentic Approach to Study Affective Polarization authors: Stephanie Anneris Malvicini, Ewelina Gajewska, Arda Derbent, Katarzyna Budzynska, Jarosław A. Chudziak, Maria Vanina Martinez year: 2026 venue: arXiv url: https://arxiv.org/abs/2603.02711 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-03-03 updated_at: 2026-03-03 status: queued relevance: high topics:

• multi-agent
• rag
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 17 collection_queries: language-agent

One-line Takeaway

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

Why Collected

• matched queries: language-agent
• inferred topics: multi-agent, rag, tool-use
• arXiv categories: cs.AI
• 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/2603.02711