307 citations · 492 across the 33 of their papers we have counts for
9 papers · 1 filter
The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality
Aileen Cheng, Alon Jacovi, Amir Globerson +62
We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually…
Training LLM Agents to Empower Humans
Evan Ellis, Vivek Myers, Jens Tuyls +3
Assistive agents should not only take actions on behalf of a human, but also step out of the way and cede control when there are important decisions to be made. However, current me…
CTRL-Rec: Controlling Recommender Systems With Natural Language
Micah Carroll, Adeline Foote, Kevin Feng +4
When users are dissatisfied with recommendations from a recommender system, they often lack fine-grained controls for changing them. Large language models (LLMs) offer a solution b…
Evaluating Sparse Autoencoders for Monosemantic Representation
Moghis Fereidouni, Muhammad Umair Haider, Peizhong Ju +1
A key barrier to interpreting large language models is polysemanticity, where neurons activate for multiple unrelated concepts. Sparse autoencoders (SAEs) have been proposed to mit…
Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety
Tomek Korbak, Mikita Balesni, Elizabeth Barnes +38
AI systems that "think" in human language offer a unique opportunity for AI safety: we can monitor their chains of thought (CoT) for the intent to misbehave. Like all other known A…
Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL
Joey Hong, Anca Dragan, Sergey Levine
Large language models (LLMs) excel in tasks like question answering and dialogue, but complex tasks requiring interaction, such as negotiation and persuasion, require additional lo…
An Approach to Technical AGI Safety and Security
Rohin Shah, Alex Irpan, Alexander Matt Turner +27
Artificial General Intelligence (AGI) promises transformative benefits but also presents significant risks. We develop an approach to address the risk of harms consequential enough…
AssistanceZero: Scalably Solving Assistance Games
Cassidy Laidlaw, Eli Bronstein, Timothy Guo +5
Assistance games are a promising alternative to reinforcement learning from human feedback (RLHF) for training AI assistants. Assistance games resolve key drawbacks of RLHF, such a…
Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following
Vivek Myers, Bill Chunyuan Zheng, Anca Dragan +2
Effective task representations should facilitate compositionality, such that after learning a variety of basic tasks, an agent can perform compound tasks consisting of multiple ste…