4 papers
LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning
Ömer Faruk Akgül, Yusuf Hakan Kalaycı, Rajgopal Kannan +2
Large reasoning models achieve strong performance on complex tasks by generating extended chains of thought, but they often "overthink": continuing to reason long after they have e…
Near-Optimal Sparsifiers for Stochastic Knapsack and Assignment Problems
Shaddin Dughmi, Yusuf Hakan Kalayci, Xinyu Liu
When uncertainty meets costly information gathering, a fundamental question emerges: which data points should we probe to unlock near-optimal solutions? Sparsification of stochasti…
Optimal Stopping vs Best-of- for Inference Time Optimization
Yusuf Kalayci, Vinod Raman, Shaddin Dughmi
Large language model (LLM) generation often requires balancing output quality against inference cost, especially when using multiple generations. We introduce a new framework for i…
Full Proportional Justified Representation
Yusuf Hakan Kalayci, Jiasen Liu, David Kempe
In multiwinner approval voting, forming a committee that proportionally represents voters' approval ballots is an essential task. The notion of justified representation (JR) demand…