6 papers
Reasoning with Sampling: Cutting at Decision Points
Felix Zhou, Anay Mehrotra, Quanquan C. Liu
Frontier reasoning models are produced by post-training base language models with reinforcement learning. Recent work has challenged this by showing that sampling from a sharpened…
QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Santiago Gonzalez, Alireza Amiri Bavandpour, Peter Ye +48
As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated evaluation. We demonstrate that st…
Edge-Private Matching Kernels Through Local Decoding
Michael Dinitz, George Z. Li, Quanquan C. Liu +1
A matching is a set of edges with no shared endpoints. We study how participants can retain useful matching structure when each knows its own relationships but those relationships…
Sublinear Space Graph Algorithms in the Continual Release Model
Alessandro Epasto, Quanquan C. Liu, Tamalika Mukherjee +1
The graph continual release model of differential privacy seeks to produce differentially private solutions to graph problems under a stream of edge updates where new private solut…
Pointwise Lipschitz Continuous Graph Algorithms
Quanquan C. Liu, Grigoris Velegkas, Yuichi Yoshida +1
In many real-world applications, it is undesirable to drastically change the problem solution after a small perturbation in the input, as unstable outputs can lead to costly transa…
Improved Massively Parallel Triangle Counting in Rounds
Quanquan C. Liu, C. Seshadhri
In this short note, we give a novel algorithm for round triangle counting in bounded arboricity graphs. Counting triangles in rounds (exactly) is listed as one of the…