Lei Sha

Table-to-Text Generation by Structure-Aware Seq2seq Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Table-to-text generation aims to generate a description for a factual table which can be viewed as a set of field-value records. To encode both the content and the structure of a table, we propose a …

DiffusionAttacker: Diffusion-Driven Prompt Manipulation for LLM Jailbreak

2024 · arXiv (Cornell University)

Large Language Models (LLMs) are susceptible to generating harmful content when prompted with carefully crafted inputs, a vulnerability known as LLM jailbreaking. As LLMs become more powerful, studying jailbreak methods is critical to enhancing security …

Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment

2025 · arXiv (Cornell University)

With rapid advancement and increasing accessibility of LLMs, fine-tuning aligned models has become a critical step for adapting them to real-world applications, which makes the safety of this fine-tuning process more important than ever. However, …

Jointly Extracting Event Triggers and Arguments by Dependency-Bridge RNN and Tensor-Based Argument Interaction

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Event extraction plays an important role in natural language processing (NLP) applications including question answering and information retrieval. Traditional event extraction relies heavily on lexical and syntactic features, which require intensive human engineering and may …