3 papers
cs.CL2026
RTD-Guard: A Black-Box Textual Adversarial Detection Framework via Replacement Token Detection
He Zhu, Yanshu Li, Wen Liu +1
Textual adversarial attacks pose a serious security threat to Natural Language Processing (NLP) systems by introducing imperceptible perturbations that mislead deep learning models…
cs.CL2026
Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM
Mengjie Liu, Jiahui Peng, Wenchang Ning +14
High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heuristic extractors are efficient,…
cs.CL2025
Topic Over Source: The Key to Effective Data Mixing for Language Models Pre-training
Jiahui Peng, Xinlin Zhuang, Jiantao Qiu +4
The performance of large language models (LLMs) is significantly affected by the quality and composition of their pre-training data, which is inherently diverse, spanning various l…