AGENTIC-SYSTEMSApril 14, 20261 min read14 views

DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

DeepReviewer 2.0 is a process-controlled agentic system that generates traceable and auditable scientific peer reviews, outperforming top-tier models like Gemini-3.1-Pro in strict issue coverage and human preference.

Computer Science > Artificial Intelligence

Title:DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

View PDF HTML (experimental)Abstract:Automated peer review is often framed as generating fluent critique, yet reviewers and area chairs need judgments they can \emph{audit}: where a concern applies, what evidence supports it, and what concrete follow-up is required. DeepReviewer~2.0 is a process-controlled agentic review system built around an output contract: it produces a \textbf{traceable review package} with anchored annotations, localized evidence, and executable follow-up actions, and it exports only after meeting minimum traceability and coverage budgets. Concretely, it first builds a manuscript-only claim--evidence--risk ledger and verification agenda, then performs agenda-driven retrieval and writes anchored critiques under an export gate. On 134 ICLR~2025 submissions under three fixed protocols, an \emph{un-finetuned 196B} model running DeepReviewer~2.0 outperforms Gemini-3.1-Pro-preview, improving strict major-issue coverage (37.26% vs.\ 23.57%) and winning 71.63% of micro-averaged blind comparisons against a human review committee, while ranking first among automatic systems in our pool. We position DeepReviewer~2.0 as an assistive tool rather than a decision proxy, and note remaining gaps such as ethics-sensitive checks.

Source: arXiv cs.AI Recent

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