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Ting Xu

7 accepted papers

2026

Understanding the Mixture-of-Experts with Nadaraya-Watson Kernel

ICLR 2026poster

Mixture-of-Experts (MoE) has become a cornerstone in recent state-of-the-art large language models (LLMs). Traditionally, MoE relies on $\mathrm{Softmax}$ as the router score function to aggregate expert output, a designed choice that has persisted from the earliest MoE models to modern LLMs, and is…

Cited by 0SourceScholar
2025

Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

ICASSP 2025accepted

The widespread adoption of face recognition has raised privacy concerns regarding the collection and use of facial data. To address this, researchers have explored "unlearnable examples" by adding imperceptible perturbations during model training to prevent the model from learning target features. H…

Cited by 0SourceScholar
2025

SeqPO-SiMT: Sequential Policy Optimization for Simultaneous Machine Translation

ACL 2025finding

We present Sequential Policy Optimization for Simultaneous Machine Translation (SeqPO-SiMT), a new policy optimization framework that defines the simultaneous machine translation (SiMT) task as a sequential decision making problem, incorporating a tailored reward to enhance translation quality while…

2024

Robust-Wide: Robust Watermarking against Instruction-driven Image Editing

ECCV 2024poster

"Instruction-driven image editing allows users to quickly edit an image according to text instructions in a forward pass. Nevertheless, malicious users can easily exploit this technique to create fake images, which could cause a crisis of trust and harm the rights of the original image owners. Water…

2023

Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction

ACL 2023findings

Aspect Sentiment Triplet Extraction (ASTE) is widely used in various applications. However, existing ASTE datasets are limited in their ability to represent real-world scenarios, hindering the advancement of research in this area. In this paper, we introduce a new dataset, named DMASTE, which is man…