Simple Words or Simple Words seminar is a registered UF’s students organization. The primary purpose of Simple Words is to bring in outstanding researchers from various areas of expertise, both in and outside the mathematics department, to discuss their work in simple words. The talk should be simple enough so that a first year graduate student or an enthusiastic undergraduate will be able to follow the main ideas of the research being conducted by the speaker. This allows early graduate students to see various topics which they can pursue en route to their degrees and encourages interaction between students and faculty in an informal setting. Moreover, students can see how their research might be used in a wide variety of applications by researchers outside the math department
Meeting Time and Venue
For Fall 2026 and Spring 2027, Talks are on Thursdays, 3:00-3:50 PM at 223 Little hall.
Scheduled for Fall 2026
| Date | Speaker, Title and Abstract |
| Sep. 17 | Speaker: Prof. Sayar Karmakar (UF, Statistics) Title: Fast segmentation of watermarked texts from large language models through epidemic change-points framework Abstract: With the growing use of large language models, concerns over content authenticity have spurred a variety of watermarking schemes. These schemes use secret keys to detect machine-generated text while remaining imperceptible to readers. Detection typically reduces to statistical hypothesis testing for the presence of watermarks, a topic that is now well studied. In contrast, the finer-grained task of localizing which segments of a text are watermarked is much less explored; existing approaches often lack scalability or guarantees robust to paraphrasing and post-editing. We bring a new perspective to this segmentation problem through the lens of epidemic change-points and, by exploiting this connection, propose WISER, a novel and computationally efficient watermark segmentation algorithm. We establish finite-sample error bounds and consistency for detecting multiple watermarked segments in a single text. Complementing these theoretical results, our extensive numerical experiments show that WISER outperforms state-of-the-art baseline methods, both in terms of computational speed as well as accuracy, on various benchmark datasets embedded with diverse watermarking schemes. Together, these theoretical and empirical results position WISER as an effective tool for watermark localization and illustrate how classical statistical ideas can yield theoretically valid and computationally efficient solutions to a modern problem of immediate importance. |
| Oct. 08 | |
| Oct. 22 |
Officers and contact
- President: Satyanath Howladar (showladar@ufl.edu)
- Vice President: Hemaho B. Taboe (hemahobeaugtaboe@ufl.edu)
- Treasurer: Dmitrii M. Smorchkov (dsmorchkov@ufl.edu)
- Secretary: Avi N. Mukhopadhyay (mukhopadhyay.avi@ufl.edu)
Feel free to email us if you have any concern!