9 citations · 9 across the 7 of their papers we have counts for
7 papers
Ski Rental with Distributional Predictions of Unknown Quality
Qiming Cui, Michael Dinitz
We revisit the central online problem of ski rental in the "algorithms with predictions" framework from the point of view of distributional predictions. Ski rental was one of the f…
Pre-trained Transformer-models using chronic invasive electrophysiology for symptom decoding without patient-individual training
Timon Merk, Saeed Salehi, Richard M. Koehler +8
Neural decoding of pathological and physiological states can enable patient-individualized closed-loop neuromodulation therapy. Recent advances in pre-trained large-scale foundatio…
Controlling tail risk in two-slope ski rental
Qiming Cui, Michael Dinitz
We study the optimal solution to a general two-slope ski rental problem with a tail risk, i.e., the chance of the competitive ratio exceeding a value is bounded by . This ex…
Measuring temporal effects of agent knowledge by date-controlled tool use
R. Patrick Xian, Qiming Cui, Stefan Bauer +1
Temporal progression is an integral part of knowledge accumulation and update. Web search is frequently adopted as grounding for agent knowledge, yet an improper configuration affe…
Robustness tests for biomedical foundation models should tailor to specifications
R. Patrick Xian, Noah R. Baker, Tom David +5
The rise of biomedical foundation models creates new hurdles in model testing and authorization, given their broad capabilities and susceptibility to complex distribution shifts. W…
7T MRI Synthesization from 3T Acquisitions
Qiming Cui, Duygu Tosun, Pratik Mukherjee +1
Supervised deep learning techniques can be used to generate synthetic 7T MRIs from 3T MRI inputs. This image enhancement process leverages the advantages of ultra-high-field MRI to…
Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks
R. Patrick Xian, Alex J. Lee, Satvik Lolla +4
The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…