arXiv (All)
open access
Dude: A Dual-Detection Multi-Agent System for Paper-Code Discrepancy Detection
LLM-empowered paper-code discrepancy detection has received growing concern since the scaling of research submissions exceeds the manual review capability. However, the limited context capacity and one-sided discrepancy detection of existing single-agent LLM paradigms lead to an inferior recall perf
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Who Wrote the Book? Detecting and Attributing LLM Ghostwriters#1156313
- Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription#153033
- RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM Safety#999446
- FLEET: From Logits Entropy to Enhanced Trajectories in Text Generation#1064201
- TRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives#1014943
Record · ID 974622
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive