activity
20232026
most citedFoundational Challenges in Assuring Alignment and Safety of Large Language Models

16 citations · 32 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CY2026

Corporate Loyalty: Some AI Systems Differentially Downplay their Creators' Controversies

Lennart Finke, Stephen Casper

Language models have become a major mediator of politically relevant information and are used to assist decision-making in high-stakes settings. Due to their wide use, the develope…

cs.CY2024★ 7 cited

Open Problems in Technical AI Governance

Anka Reuel, Ben Bucknall, Stephen Casper +30

AI progress is creating a growing range of risks and opportunities, but it is often unclear how they should be navigated. In many cases, the barriers and uncertainties faced are at…

cs.LG2024

The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability

Stephen Casper, Jieun Yun, Joonhyuk Baek +13

Interpretability techniques are valuable for helping humans understand and oversee AI systems. The SaTML 2024 CNN Interpretability Competition solicited novel methods for studying…

cs.LG2024★ 16 cited

Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Usman Anwar, Abulhair Saparov, Javier Rando +39

This work identifies 18 foundational challenges in assuring the alignment and safety of large language models (LLMs). These challenges are organized into three different categories…

cs.CL2023★ 9 cited

Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation

Rusheb Shah, Quentin Feuillade--Montixi, Soroush Pour +3

Despite efforts to align large language models to produce harmless responses, they are still vulnerable to jailbreak prompts that elicit unrestricted behaviour. In this work, we in…