output
20132026
most citedDueling Network Architectures for Deep Reinforcement Learning

1.8k citations

114 papers

cs.AI2026

Synthetic Counteradaptation: A Principle of Human-AI Co-evolution

Ivar Frisch, Jackie Kay, Philip Moreira Tomei

In this paper, we introduce the concept of synthetic counteradaptation, a process where human and AI systems co-evolve by adapting to each other's strategies and behaviors. Synthet…

physics.plasm-ph2026

Applications of a novel model-based real-time observer for electron density profile control experiments in TCV

F. Pastore, O. Sauter, F. Felici +12

Real-time control of tokamak plasmas encompasses sustaining a high-performance stationary state, avoiding disruptions, and managing ramp-up and ramp-down phases. Real-time estimati…

cs.HC2025★ 13 cited

Sensible Agent: A Framework for Unobtrusive Interaction with Proactive AR Agents

Geonsun Lee, Min Xia, Nels Numan +9

Proactive AR agents promise context-aware assistance, but their interactions often rely on explicit voice prompts or responses, which can be disruptive or socially awkward. We intr…

astro-ph.IM2025★ 9 cited

Improving cosmological reach of a gravitational wave observatory using Deep Loop Shaping

Jonas Buchli, Brendan Tracey, Tomislav Andric +28

Improved low-frequency sensitivity of gravitational wave observatories would unlock study of intermediate-mass black hole mergers, binary black hole eccentricity, and provide early…

stat.ML2025

Optimal Stopping in Latent Diffusion Models

Yu-Han Wu, Quentin Berthet, Gérard Biau +3

We identify and analyze a surprising phenomenon of Latent Diffusion Models (LDMs) where the final steps of the diffusion can degrade sample quality. In contrast to conventional arg…

cs.CY2025★ 26 cited

We Need a New Ethics for a World of AI Agents

Iason Gabriel, Geoff Keeling, Arianna Manzini +1

The deployment of capable AI agents raises fresh questions about safety, human-machine relationships and social coordination. We argue for greater engagement by scientists, scholar…