Think Together

T.R. Davidson 

Many critical problems involve distributed information that must be synthesized under severe time constraints. This necessitates a shift away from massive models toward small, specialized agents capable of dynamic communication. We label these scenarios "BotMapReduce" problems and explore how high-speed, multi-model coordination could shift the future of AI development.

TL;DR: Many important problems require agentic cooperation
MAR 2026  |  10 MIN READ

The Collaboration Gap

T.R. Davidson, A. Fourney, S. Amershi, R. West, E. Horvitz, E. Kamar

   🎓 arXiv paper

Imagine hanging up a frame in your living room. You and a friend naturally divide the work, clarify confusing instructions, and adapt if a screw is missing. We expect this type of fluid, on-the-fly teamwork from humans, but can today’s AI agents do the same? Well, not quite.

TL;DR: Exploring the challenges of dynamic agentic collaboration
NOV 2025  |  10 MIN READ

Self-Recognition in Language Models

T.R. Davidson, V. Surkov, V. Veselovsky, G. Russo, R. West, C. Gulcehre

   🎓 arXiv paper   🤖 GitHub repository   📰 IEEE Spectrum article

A rapidly growing number of applications is being built on just a few frontier LMs. This dependency might introduce novel security risks if LMs develop self-recognition capabilities. Inspired by human verification methods, we assess self-recognition in LMs using model-generated "security questions".

TL;DR: Novel insights on self-recognition and position bias in LMs
SEP 2024  |  10 MIN READ