Search Results for author:
Found 7 papers, 4 papers with code
InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification
Large Language Models (LLMs) have demonstrated remarkable proficiency in a wide range of NLP tasks.
ToxiCloakCN: Evaluating Robustness of Offensive Language Detection in Chinese with Cloaking Perturbations
Detecting hate speech and offensive language is essential for maintaining a safe and respectful digital environment.
Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification
Authorship verification (AV) is a fundamental task in natural language processing (NLP) and computational linguistics, with applications in forensic analysis, plagiarism detection, and identification of deceptive content.
Yelp Reviews and Food Types: A Comparative Analysis of Ratings, Sentiments, and Topics
This study examines the relationship between Yelp reviews and food types, investigating how ratings, sentiments, and topics vary across different types of food.
Knowledge-refined Denoising Network for Robust Recommendation
Knowledge graph (KG), which contains rich side information, becomes an essential part to boost the recommendation performance and improve its explainability.
Non-rigid Point Cloud Registration for Middle Ear Diagnostics with Endoscopic Optical Coherence Tomography
To overcome the lack of labeled training data, a fast and effective generation pipeline in Blender3D is designed to simulate middle ear shapes and extract in-vivo noisy and partial point clouds.
Self-Guided Learning to Denoise for Robust Recommendation
Besides, our method can automatically switch its learning phase at the memorization point from memorization to self-guided learning, and select clean and informative memorized data via a novel adaptive denoising scheduler to improve the robustness.
