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researcher

Daniel Kang

6 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author3

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.CV1
  • cs.DB1
ORCID 0000-0001-9860-9938
same name
  • Daniel Kang — 15 papers, h 24
  • Daniel Kang — 13 papers, h 7
  • Daniel Kang — 4 papers
  • Daniel Kang — 3 papers, h 2
  • Daniel Kang — 1 paper
  • Daniel Kang — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedExploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks

27 citations · 62 across the 6 of their papers we have counts for

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2024★ 14 cited

LLM Agents can Autonomously Exploit One-day Vulnerabilities

Richard Fang, Rohan Bindu, Akul Gupta +1

LLMs have becoming increasingly powerful, both in their benign and malicious uses. With the increase in capabilities, researchers have been increasingly interested in their ability…

cs.CR2024★ 1 cited

Trustless Audits without Revealing Data or Models

Suppakit Waiwitlikhit, Ion Stoica, Yi Sun +2

There is an increasing conflict between business incentives to hide models and data as trade secrets, and the societal need for algorithmic transparency. For example, a rightsholde…

cs.CR2024★ 10 cited

LLM Agents can Autonomously Hack Websites

Richard Fang, Rohan Bindu, Akul Gupta +2

In recent years, large language models (LLMs) have become increasingly capable and can now interact with tools (i.e., call functions), read documents, and recursively call themselv…

cs.CR2023★ 27 cited

Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks

Daniel Kang, Xuechen Li, Ion Stoica +3

Recent advances in instruction-following large language models (LLMs) have led to dramatic improvements in a range of NLP tasks. Unfortunately, we find that the same improved capab…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.