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20212026
most citedGetting aligned on representational alignment

35 citations · 68 across the 26 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CY2025★ 2 cited

Measuring and mitigating overreliance to build human-compatible AI

Lujain Ibrahim, Katherine M. Collins, Sunnie S. Y. Kim +14

Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable of engaging more fluidly in natural lan…

cs.CY2025

Documenting Deployment with Fabric: A Repository of Real-World AI Governance

Mackenzie Jorgensen, Kendall Brogle, Katherine M. Collins +10

Artificial intelligence (AI) is increasingly integrated into society, from financial services and traffic management to creative writing. Academic literature on the deployment of A…

q-bio.NC2025

Using LLMs to Advance the Cognitive Science of Collectives

Ilia Sucholutsky, Katherine M. Collins, Nori Jacoby +2

LLMs are already transforming the study of individual cognition, but their application to studying collective cognition has been underexplored. We lay out how LLMs may be able to a…

cs.AI2025

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships

Kerem Oktar, Katherine M. Collins, Jose Hernandez-Orallo +4

Artificial Intelligence (AI) systems have historically been used as tools that execute narrowly defined tasks. Yet recent advances in AI have unlocked possibilities for a new class…

cs.MA2025

When Should We Orchestrate Multiple Agents?

Umang Bhatt, Sanyam Kapoor, Mihir Upadhyay +6

Strategies for orchestrating the interactions between multiple agents, both human and artificial, can wildly overestimate performance and underestimate the cost of orchestration. W…

cs.AI2025

On Benchmarking Human-Like Intelligence in Machines

Lance Ying, Katherine M. Collins, Lionel Wong +6

Recent advances in Artificial Intelligence (AI) have yielded powerful computational models that, by learning from vast amounts of human-generated data, are increasingly posited as…

cs.AI2025

Revisiting Rogers' Paradox in the Context of Human-AI Interaction

Katherine M. Collins, Umang Bhatt, Ilia Sucholutsky

Humans learn about the world, and how to act in the world, in many ways: from individually conducting experiments to observing and reproducing others' behavior. Different learning…