most citedHarnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

PPBoost: Progressive Prompt Boosting for Text-Driven Medical Image Segmentation

Xuchen Li, Hengrui Gu, Mohan Zhang +6

Text-prompted foundation models for medical image segmentation offer an intuitive way to delineate anatomical structures from natural language queries, but their predictions often…

cs.LG20251 cited

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification

Ruxue Shi, Hengrui Gu, Xu Shen +1

Large Language Models (LLMs) have shown remarkable ability in solving complex tasks, making them a promising tool for enhancing tabular learning. However, existing LLM-based method…

cs.LG2025

Latte: Transfering LLMs` Latent-level Knowledge for Few-shot Tabular Learning

Ruxue Shi, Hengrui Gu, Hangting Ye +3

Few-shot tabular learning, in which machine learning models are trained with a limited amount of labeled data, provides a cost-effective approach to addressing real-world challenge…

cs.CR2025

Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense

Yang Ouyang, Hengrui Gu, Shuhang Lin +6

As large language models (LLMs) are increasingly deployed in diverse applications, including chatbot assistants and code generation, aligning their behavior with safety and ethical…

cs.CL2024

Pioneering Reliable Assessment in Text-to-Image Knowledge Editing: Leveraging a Fine-Grained Dataset and an Innovative Criterion

Hengrui Gu, Kaixiong Zhou, Yili Wang +2

During pre-training, the Text-to-Image (T2I) diffusion models encode factual knowledge into their parameters. These parameterized facts enable realistic image generation, but they…