6 papers
ConvexBench: Can LLMs Recognize Convex Functions?
Yepeng Liu, Yu Huang, Yu-Xiang Wang +2
Convex analysis is a modern branch of mathematics with many applications. As Large Language Models (LLMs) start to automate research-level math and sciences, it is important for LL…
A Reinforcement Learning Framework for Robust and Secure LLM Watermarking
Li An, Yujian Liu, Yepeng Liu +3
Watermarking has emerged as a promising solution for tracing and authenticating text generated by large language models (LLMs). A common approach to LLM watermarking is to construc…
SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting
Yang Xing, Jiong Wu, Yuheng Bu +1
Although new vision foundation models such as Segment Anything Model 2 (SAM2) have significantly enhanced zero-shot image segmentation capabilities, reliance on human-provided prom…
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber +1
Despite substantial progress in promoting fairness in high-stake applications using machine learning models, existing methods often modify the training process, such as through reg…
Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learning
Li An, Yujian Liu, Yepeng Liu +3
Watermarking has emerged as a promising technique for detecting texts generated by LLMs. Current research has primarily focused on three design criteria: high quality of the waterm…
Distributional Information Embedding: A Framework for Multi-bit Watermarking
Haiyun He, Yepeng Liu, Ziqiao Wang +2
This paper introduces a novel problem, distributional information embedding, motivated by the practical demands of multi-bit watermarking for large language models (LLMs). Unlike t…