Writing effective rebuttals is a high-stakes task that demands more than linguistic fluency, as it requires precise alignment between reviewer intent and manuscript details. Current solutions typically treat this as a direct-to-text generation problem, suffering from hallucination, overlooked critiques, and a lack of verifiable grounding. To address these limitations, we introduce $\textbf{RebuttalAgent}$, the first multi-agents framework that reframes rebuttal generation as an evidence-centr...
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---
name: paper2rebuttal-a-multi-agent-framework-for
title: "Paper2Rebuttal: A Multi-Agent Framework for Transparent Author Response Generation"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.14171"
keywords: [Agent]
description: "Writing effective rebuttals is a high-stakes task that demands more than linguistic fluency, as it requires precise alignment between reviewer intent and manuscript details. Current solutions typically treat this as a direct-to-text generation problem, suffering from hallucination, overlooked critiques, and a lack of verifiable grounding. To address these limitations, we introduce $\textbf{RebuttalAgent}$, the first multi-agents framework that reframes rebuttal generation as an evidence-centric ..."
---
## Overview
This skill covers paper2rebuttal: a multi-agent framework for transparent author response generation. It addresses critical challenges in autonomous agent development.
## Key Concepts
The paper introduces novel approaches to:
- Agent evaluation and benchmarking
- Improving agent efficiency and reasoning
- Designing robust agent systems
## When to Use
Use this when working on:
- Agent-based systems and evaluation
- Autonomous reasoning and planning
- Multi-agent frameworks
## When NOT to Use
- Non-agent applications
- Tasks requiring implementation code (see the paper)
## References
- Paper: https://arxiv.org/abs/2601.14171
- PDF: https://arxiv.org/pdf/2601.14171
