When Your Reviewer is an LLM: Biases, Divergence, and Prompt Injection Risks in Peer Review
Fuente:
arXiv
Saved in:
| Main Authors: | Zhu, Changjia, Xiong, Junjie, Ma, Renkai, Lu, Zhicong, Liu, Yao, Li, Lingyao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers
by: Li, Lingyao, et al.
Published: (2026)
by: Li, Lingyao, et al.
Published: (2026)
Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models
by: Xiong, Junjie, et al.
Published: (2025)
by: Xiong, Junjie, et al.
Published: (2025)
COGNITION: From Evaluation to Defense against Multimodal LLM CAPTCHA Solvers
by: Wang, Junyu, et al.
Published: (2025)
by: Wang, Junyu, et al.
Published: (2025)
Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy
by: Gudiño-Rosero, Jairo, et al.
Published: (2025)
by: Gudiño-Rosero, Jairo, et al.
Published: (2025)
Misleading Large Language Models used (or misused) in Scientific Peer-Reviewing via Hidden Prompt-Injection Attacks
by: Collu, Matteo Gioele, et al.
Published: (2025)
by: Collu, Matteo Gioele, et al.
Published: (2025)
From Prompt Injections to SQL Injection Attacks: How Protected is Your LLM-Integrated Web Application?
by: Pedro, Rodrigo, et al.
Published: (2023)
by: Pedro, Rodrigo, et al.
Published: (2023)
AI Agents May Always Fall for Prompt Injections
by: Abdelnabi, Sahar, et al.
Published: (2026)
by: Abdelnabi, Sahar, et al.
Published: (2026)
Fingerprinting LLMs via Prompt Injection
by: Hu, Yuepeng, et al.
Published: (2025)
by: Hu, Yuepeng, et al.
Published: (2025)
AttriGuard: Defeating Indirect Prompt Injection in LLM Agents via Causal Attribution of Tool Invocations
by: He, Yu, et al.
Published: (2026)
by: He, Yu, et al.
Published: (2026)
Democratizing Federated Learning with Blockchain and Multi-Task Peer Prediction
by: Witt, Leon, et al.
Published: (2026)
by: Witt, Leon, et al.
Published: (2026)
When Reject Turns into Accept: Quantifying the Vulnerability of LLM-Based Scientific Reviewers to Indirect Prompt Injection
by: Sahoo, Devanshu, et al.
Published: (2025)
by: Sahoo, Devanshu, et al.
Published: (2025)
When Skills Lie: Hidden-Comment Injection in LLM Agents
by: Wang, Qianli, et al.
Published: (2026)
by: Wang, Qianli, et al.
Published: (2026)
What's on Your Mind? Exploring Privacy of Mental Health Apps
by: Georgiou, Chloe, et al.
Published: (2026)
by: Georgiou, Chloe, et al.
Published: (2026)
Cybersecurity Career Requirements: A Literature Review
by: Nkongolo, Mike, et al.
Published: (2023)
by: Nkongolo, Mike, et al.
Published: (2023)
The Vulnerability of LLM Rankers to Prompt Injection Attacks
by: Yin, Yu, et al.
Published: (2026)
by: Yin, Yu, et al.
Published: (2026)
Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research
by: An, Heajun, et al.
Published: (2025)
by: An, Heajun, et al.
Published: (2025)
A Comprehensive Analytical Review on Cybercrime in West Africa
by: Adewopo, Victor, et al.
Published: (2024)
by: Adewopo, Victor, et al.
Published: (2024)
A Systematic Literature Review on the NIS2 Directive
by: Ruohonen, Jukka
Published: (2024)
by: Ruohonen, Jukka
Published: (2024)
Global Web, Local Privacy? An International Review of Web Tracking
by: Yu, Harry, et al.
Published: (2026)
by: Yu, Harry, et al.
Published: (2026)
BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers?
by: Jiang, Fengqing, et al.
Published: (2025)
by: Jiang, Fengqing, et al.
Published: (2025)
Prompt Injection Attack to Tool Selection in LLM Agents
by: Shi, Jiawen, et al.
Published: (2025)
by: Shi, Jiawen, et al.
Published: (2025)
Cybersecurity Guidance for Smart Homes: A Cross-National Review of Government Sources
by: Jüttner, Victor, et al.
Published: (2026)
by: Jüttner, Victor, et al.
Published: (2026)
"Give a Positive Review Only": An Early Investigation Into In-Paper Prompt Injection Attacks and Defenses for AI Reviewers
by: Zhou, Qin, et al.
Published: (2025)
by: Zhou, Qin, et al.
Published: (2025)
Detecting LLM-Generated Peer Reviews
by: Rao, Vishisht, et al.
Published: (2025)
by: Rao, Vishisht, et al.
Published: (2025)
When AI Meets the Web: Prompt Injection Risks in Third-Party AI Chatbot Plugins
by: Kaya, Yigitcan, et al.
Published: (2025)
by: Kaya, Yigitcan, et al.
Published: (2025)
ObliInjection: Order-Oblivious Prompt Injection Attack to LLM Agents with Multi-source Data
by: Wang, Reachal, et al.
Published: (2025)
by: Wang, Reachal, et al.
Published: (2025)
AgentVisor: Defending LLM Agents Against Prompt Injection via Semantic Virtualization
by: Ying, Zonghao, et al.
Published: (2026)
by: Ying, Zonghao, et al.
Published: (2026)
SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization
by: Liu, Houjun, et al.
Published: (2026)
by: Liu, Houjun, et al.
Published: (2026)
Towards Trustworthy AI: Characterizing User-Reported Risks across LLMs "In the Wild"
by: Li, Lingyao, et al.
Published: (2025)
by: Li, Lingyao, et al.
Published: (2025)
Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs
by: Wang, Jiawen, et al.
Published: (2025)
by: Wang, Jiawen, et al.
Published: (2025)
What to Consider When Considering Differential Privacy for Policy
by: Nanayakkara, Priyanka, et al.
Published: (2024)
by: Nanayakkara, Priyanka, et al.
Published: (2024)
Review-Incorporated Model-Agnostic Profile Injection Attacks on Recommender Systems
by: Yang, Shiyi, et al.
Published: (2024)
by: Yang, Shiyi, et al.
Published: (2024)
To Protect the LLM Agent Against the Prompt Injection Attack with Polymorphic Prompt
by: Wang, Zhilong, et al.
Published: (2025)
by: Wang, Zhilong, et al.
Published: (2025)
SoK: Reviewing Two Decades of Security, Privacy, Accessibility, and Usability Studies on Internet of Things for Older Adults
by: Saka, Suleiman, et al.
Published: (2025)
by: Saka, Suleiman, et al.
Published: (2025)
SafeReview: Defending LLM-based Review Systems Against Adversarial Hidden Prompts
by: Xin, Yuan, et al.
Published: (2026)
by: Xin, Yuan, et al.
Published: (2026)
How Safe Is Your Data in Connected and Autonomous Cars: A Consumer Advantage or a Privacy Nightmare ?
by: Chougule, Amit, et al.
Published: (2026)
by: Chougule, Amit, et al.
Published: (2026)
Silent Egress: When Implicit Prompt Injection Makes LLM Agents Leak Without a Trace
by: Lan, Qianlong, et al.
Published: (2026)
by: Lan, Qianlong, et al.
Published: (2026)
SemFuzz: A Semantics-Aware Fuzzing Framework for Network Protocol Implementations
by: Sun, Yanbang, et al.
Published: (2026)
by: Sun, Yanbang, et al.
Published: (2026)
Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage
by: Wang, Qin, et al.
Published: (2024)
by: Wang, Qin, et al.
Published: (2024)
Prompt injections as a tool for preserving identity in GAI image descriptions
by: Glazko, Kate, et al.
Published: (2025)
by: Glazko, Kate, et al.
Published: (2025)
Similar Items
-
LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers
by: Li, Lingyao, et al.
Published: (2026) -
Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models
by: Xiong, Junjie, et al.
Published: (2025) -
COGNITION: From Evaluation to Defense against Multimodal LLM CAPTCHA Solvers
by: Wang, Junyu, et al.
Published: (2025) -
Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy
by: Gudiño-Rosero, Jairo, et al.
Published: (2025) -
Misleading Large Language Models used (or misused) in Scientific Peer-Reviewing via Hidden Prompt-Injection Attacks
by: Collu, Matteo Gioele, et al.
Published: (2025)