activity
20172026
most citedRandomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear (Sometimes Sublinear) Running Time

19 citations · 19 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CR2026

Anchor-ECC: Local Integrity Checking for Watermarked LLM Outputs via Error-Correcting Codes

Zewei Deng, Muhammad Siddeek, Liyan Xie +4

LLM watermarking has become an effective approach to distinguishing AI-generated text from human-written text by embedding detectable patterns during generation. However, a small p…

cs.LG2025

Detecting Post-generation Edits to Watermarked LLM Outputs via Combinatorial Watermarking

Liyan Xie, Muhammad Siddeek, Mohamed Seif +2

Watermarking has become a key technique for proprietary language models, enabling the distinction between AI-generated and human-written text. However, in many real-world scenarios…

cs.LG2025

Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias

Rui Lu, Runzhe Wang, Kaifeng Lyu +3

Score-based diffusion models have achieved incredible performance in generating realistic images, audio, and video data. While these models produce high-quality samples with impres…

math.NT2025

Local divisor correlations in almost all short intervals

Javier Pliego, Yu-Chen Sun, Mengdi Wang

Let be natural numbers, and let denote the -fold and -fold divisor functions, respectively. We analyse the asymptotic behavior of the sum $\sum_{x<n\l…

math.NT2024

Local Fourier uniformity of higher divisor functions on average

Mengdi Wang

Let be the -fold divisor function. By constructing an approximant of , denoted as , which is a normalized truncation of the -fold divisor function, we prove…

math.OC2017★ 19 cited

Randomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear (Sometimes Sublinear) Running Time

Mengdi Wang

We propose a novel randomized linear programming algorithm for approximating the optimal policy of the discounted Markov decision problem. By leveraging the value-policy duality an…