5 accepted papers
Evaluating text-to-vision content hinges on two crucial aspects: **visual quality** and **alignment**. While significant progress has been made in developing objective models to assess these dimensions, the performance of such models heavily relies on the scale and quality of human annotations. Acco…
Large Language Models (LLMs) have shown impressive capabilities across various tasks but remain vulnerable to meticulously crafted jailbreak attacks. In this paper, we identify a critical safety gap: while LLMs are adept at detecting jailbreak prompts, they often produce unsafe responses when direct…
We consider the problem of estimating the directions of multiple target sources by exploiting auxiliary sources, focusing on a single snapshot obtained by the distributed array with position errors and angular offsets of subarrays. Former calibration methods generally assume the directions of auxili…
Previous works of negation understanding mainly focus on negation cue detection and scope resolution, without identifying negation subject which is also significant to the downstream tasks. In this paper, we propose a new negation triplet extraction (NTE) task which aims to extract negation subject…
Entity alignment (EA) aims to discover the equivalent entity pairs between KGs, which is a crucial step for integrating multi-source KGs.For a long time, most researchers have regarded EA as a pure graph representation learning task and focused on improving graph encoders while paying little attenti…