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

---
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