7 citations · 7 across the 7 of their papers we have counts for
9 papers
Decouple to Forget: Semantic Mediation for Sensitive Unlearning in Large Language Models
Jingyue Cong, Andy Song, Yang Yu +7
Machine unlearning for large language models seeks to remove specified knowledge while preserving general capability, yet current methods often treat an entire response as the unit…
Negative Entity Suppression for Zero-Shot Captioning with Synthetic Images
Zimao Lu, Hui Xu, Bing Liu +1
Text-only training provides an attractive approach to address data scarcity challenges in zero-shot image captioning (ZIC), avoiding the expense of collecting paired image-text ann…
Fine-Tuning Large Multimodal Models for Automatic Pronunciation Assessment
Ke Wang, Wenning Wei, Yan Deng +2
Automatic Pronunciation Assessment (APA) is critical for Computer-Assisted Language Learning (CALL), requiring evaluation across multiple granularities and aspects. Large Multimoda…
Exploring the Potential of Large Multimodal Models as Effective Alternatives for Pronunciation Assessment
Ke Wang, Lei He, Kun Liu +3
Large Multimodal Models (LMMs) have demonstrated exceptional performance across a wide range of domains. This paper explores their potential in pronunciation assessment tasks, with…
Deep Contrastive Unlearning for Language Models
Estrid He, Tabinda Sarwar, Ibrahim Khalil +2
The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual data and generating human-like language…
LLaVA-Zip: Adaptive Visual Token Compression with Intrinsic Image Information
Ke Wang, Hong Xuan
Multi-modal large language models (MLLMs) utilizing instruction-following data, such as LLaVA, have achieved great progress in the industry. A major limitation in these models is t…
A Survey on Data Synthesis and Augmentation for Large Language Models
Ke Wang, Jiahui Zhu, Minjie Ren +8
The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation. However, the growth rate o…
E-ANT: A Large-Scale Dataset for Efficient Automatic GUI NavigaTion
Ke Wang, Tianyu Xia, Zhangxuan Gu +5
Online GUI navigation on mobile devices has driven a lot of attention recent years since it contributes to many real-world applications. With the rapid development of large languag…
Improving Neural Machine Translation by Multi-Knowledge Integration with Prompting
Ke Wang, Jun Xie, Yuqi Zhang +1
Improving neural machine translation (NMT) systems with prompting has achieved significant progress in recent years. In this work, we focus on how to integrate multi-knowledge, mul…