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Adversarial Scalable Oversight for Truthfulness

Samuel R. Bowman

12/2023

Oversight

Epistemic Side Effects

Sheila McIlraith

12/2023

Studying LLM Generalization through Influence Functions

Roger Grosse

12/2023

Interpretability

Out of Context Reasoning in LLMs

Owain Evans

12/2023

Multi-Agent Risks from Advanced AI

Lewis Hammond

12/2023

Governance

Provably Safe AI

Max Tegmark

12/2023

Oversight

Adversarial Examples Transfer from Machines to Humans

Jascha Sohl-Dickstein

12/2023

Robustness

Mechanistic Interpretability of In-Context Learning

Johannes von Oswald

12/2023

Interpretability

Keeping Humans in the Loop

John Schulman

12/2023

Governance

Heuristic Arguments: An Approach to Detecting Anomalous Model

Eric Neyman

12/2023

Robustness

Building an Off Switch for AI

Gillian Hadfield

12/2023

Governance

The Quantization Model of Neural Scaling

Eric J. Michaud

12/2023

Interpretability

Complex Systems View of Large-Scale AI systems

Irina Rish

12/2023

Governance

Preference Learning in Alignment

Dylan Hadfield-Menell

12/2023

Oversight

AI Safety by Debate via Regret Minimization

Elad Hazan

12/2023

Oversight

The Challenge of Monitoring Covert Interactions and Behavioral Shifts in LLM Agents

Dimitris Papailiopoulos

12/2023

Robustness

Sociotechnical AI safety

David Krueger

12/2023

The Impossibility of (Strong) Watermarking

Boaz Barak

12/2023

Robustness

Secret Collusion Among Generative AI Agents

Christian Schroeder de Witt

12/2023

Robustness

Weak-to-Strong Generalization

Collin Burns

12/2023

Robustness

Your RLHF fine-tuning is Secretly Applying a Regret Preference

Brad Knox

12/2023

Oversight

Theories and Tools for Mechanistic Interpretability via Causal Abstraction

Atticus Geiger

12/2023

Interpretability

Optimized Misalignment

Anca Dragan

12/2023

Oversight

Alignment and Interpretability: How we Might Get It right

Been Kim

12/2023

Interpretability

Preparedness @ OpenAl

Aleksander Madry

12/2023

Governance

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