agent/papers/items/2025-2511-11169-refine-and-align-confidence-calibration-through-multi-agent-interaction-in-vqa.md

Paper: Refine and Align: Confidence Calibration through Multi-Agent Interaction in VQA

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type: paper title: "Refine and Align: Confidence Calibration through Multi-Agent Interaction in VQA" authors: Ayush Pandey, Jai Bardhan, Ishita Jain, Ramya S Hebbalaguppe, Rohan Raju Dhanakshirur, Lovekesh Vig year: 2025 venue: arXiv url: https://arxiv.org/abs/2511.11169 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2025-11-14 updated_at: 2025-11-14 status: queued relevance: high topics:

• agent-evaluation
• embodied-agent
• multi-agent
• tool-use methods:

benchmarks:

models:

datasets:

• cs.CV
• cs.AI
• cs.LG related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: function-calling

One-line Takeaway

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

Why Collected

• matched queries: function-calling
• inferred topics: agent-evaluation, embodied-agent, multi-agent, tool-use
• arXiv categories: cs.CV, cs.AI, cs.LG
• collection score: 16

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/2511.11169