most citedModeling dissipation in quantum active matter

1 citations

17 papers

cs.LG2026

Task- and dataset-specific information in protein language models

Roman Joeres, Ilya Senatorov, Olga V. Kalinina +2

Protein language models (PLMs) have transferred the latest advances from natural language processing to computational biology. These models, trained on large corpora of protein seq…

cs.CL2026

PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models

Zhanna Mukhametsharip, Vera Demberg, Varsha Suresh

Large Vision-Language Models (LVLMs) have demonstrated strong performance on multimodal benchmarks, yet it remains unclear whether they genuinely reason about relationships between…

quant-ph20261 cited

Quantum max-flow in the bridge graph

Fulvio Gesmundo, Vladimir Lysikov, Vincent Steffan

The quantum max-flow is a linear algebraic version of the classical max-flow of a graph, used in quantum many-body physics to quantify the maximal possible entanglement between two…

quant-ph20261 cited

Modeling dissipation in quantum active matter

Alexander P. Antonov, Sangyun Lee, Benno Liebchen +5

Active matter is characterized by a constant influx and dissipation of energy that gives rise to directed motion. Dissipation requires interactions with an external environment, su…

cond-mat.soft2026

Collective chemotactic search

Adam Wysocki, Hugues Meyer, Heiko Rieger

We investigate collective search by self-propelled agents that are repelled by their own chemically produced trails, a minimal mechanism that simultaneously generates indirect inte…

cs.HC2026

Mind the Trust Gap: Identifying (Mis)alignments in Teacher-Student Views Toward Control and Agency in K-12 Classroom AI

Tomohiro Nagashima, Lisa Siegrist, Niklas Scholz +3

As Artificial Intelligence (AI)-based technologies have been integrated into school classrooms where multiple stakeholders (with different roles) interact with each other, it is cr…