Songsheng Wang — accepted AI-conference papers

2025

HiMATE: A Hierarchical Multi-Agent Framework for Machine Translation Evaluation

Shijie Zhang, Renhao Li, Songsheng Wang, Philipp Koehn, Min Yang, Derek F. Wong

EMNLP 2025

The advancement of Large Language Models (LLMs) enables flexible and interpretable automatic evaluations. In the field of machine translation evaluation, utilizing LLMs with translation error annotations based on Multidimensional Quality Metrics (MQM) yields more human-aligned judgments. However, cu

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2025

Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance

Songsheng Wang, Rucheng Yu, Zhihang Yuan, Chao Yu, Feng Gao, Yu Wang +1

EMNLP 2025

Vision-Language-Action (VLA) models have made substantial progress by leveraging the robust capabilities of Visual Language Models (VLMs). However, VLMs’ significant parameter size and autoregressive (AR) decoding nature impose considerable computational demands on VLA models. While Speculative Deco

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