1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Command-V: Pasting LLM Behaviors via Activation Profiles
Barry Wang, Avi Schwarzschild, Alexander Robey +4
Retrofitting large language models (LLMs) with new behaviors typically requires full finetuning or distillation-costly steps that must be repeated for every architecture. In this w…
FictionalQA: A Dataset for Studying Memorization and Knowledge Acquisition
John Kirchenbauer, Janny Mongkolsupawan, Yuxin Wen +2
When language models are trained on textual data, they acquire both knowledge about the structure of language as well as knowledge of facts about the world. At inference time, thei…
LLMs unlock new paths to monetizing exploits
Nicholas Carlini, Milad Nasr, Edoardo Debenedetti +5
We argue that Large language models (LLMs) will soon alter the economics of cyberattacks. Instead of attacking the most commonly used software and monetizing exploits by targeting…
Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos +10
It is now common to evaluate Large Language Models (LLMs) by having humans manually vote to evaluate model outputs, in contrast to typical benchmarks that evaluate knowledge or ski…