4 citations · 7 across the 10 of their papers we have counts for
4 papers · 1 filter
Training-Free Prompt Selection for Efficient Reinforcement Learning With Partial Rollouts
Lei Jiang, Honghui Bao, Yue Zhou +3
Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for training reasoning models, but its computational cost makes efficient data selection i…
A Bayesian Correlated Equilibrium for Early Insider-Threat Detection
Javed M. Shah, Ian A. Kash, Natalie Parde
We model insider threat detection as a dynamic Bayesian game in which a platform coordinates a committee of strategic certifiers to sustain equilibrium among honest users and detec…
Behind the [MASK]: Disentangling Representation and Faithfulness in DAPF-Based Dementia Detection
Pardis Ranjbar-Noiey, Natalie Parde
Spoken-language analysis via prompt-based domain-adaptive models is a promising direction for low-resource, non-invasive dementia screening, but such models remain internally opaqu…
UIC-AIHealth4All at ArchEHR-QA 2026: Answer-First Evidence Grounding for Clinical Question Answering
Mohammad Arvan, Hossein Haeri, Natalie Parde +1
We describe the UIC-AIHealth4All system for ArchEHR-QA 2026, a shared task on grounded question answering from electronic health records. We participated in Subtasks 2 (evidence id…