Papers by Zixiao Wang

3 papers
ATFormer: A Learned Performance Model with Transfer Learning Across Devices for Deep Learning Tensor Programs (2023.emnlp-main)

Copied to clipboard

Challenge: Compilation-based methods with performance models have poor measurement accuracy and transferability between platforms.
Approach: They propose a compiler that automatically generates tensors and automatically tunes them for different hardware platforms.
Outcome: The proposed model reduces inference time and costs on modern DNN benchmarks.
GlossaGen: Making Academic Translation Smarter with Glossing (2026.findings-acl)

Copied to clipboard

Challenge: Existing machine translation systems obscure or mistranslate key terminology, while paraphrasing aimed at lay readers often oversimplifies it, hindering their ability to master domain-specific technical vocabulary.
Approach: They propose a task which produces translations dynamically adapted to a reader’s academic proficiency, or level, and a framework to address this challenge.
Outcome: The proposed framework achieves higher scores than baselines on a synthesized benchmark and human evaluations.
Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs (2025.findings-acl)

Copied to clipboard

Challenge: Existing approaches to persona simulation large language models (LLMs) focus on learning basic biographical information, or using limited role-play dialogue datasets to capture a character’s responses.
Approach: They propose to train characters using a linguistic structure and a style-tuning mechanism that allows a general linguistic style expert to collaborate with other task-specific experts to better understand their thoughts.
Outcome: The proposed model outperforms baselines on linguistic accuracy and opinion comprehension on three tasks for Lu Xun's essay collection.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations