Papers by Akul Gupta

2 papers
Teams of LLM Agents can Exploit Zero-Day Vulnerabilities (2026.eacl-long)

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Challenge: Existing frameworks for LLM agents fail to exploit real-world zero-day vulnerabilities . prior work has shown that simple agents can hack mock "capture-the-flag" websites .
Approach: They propose a system of agents with a planning agent that can launch subagents to exploit real-world vulnerabilities.
Outcome: The proposed framework improves over previous frameworks by up to 4.3 on 14 real-world vulnerabilities.
Removing RLHF Protections in GPT-4 via Fine-Tuning (2024.naacl-short)

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Challenge: Large language models (LLMs) have increased in their capabilities, which increases their potential for dual use.
Approach: They show that fine-tuning can remove RLHFprotections with as few as 340 examples and a 95% success rate.
Outcome: The proposed method removes RLHFprotections with as few as 340 examples and a 95% success rate on non-censored outputs.

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