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cs.CL2025

Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models

Minghan Wang, Thuy-Trang Vu, Yuxia Wang +2

Simultaneous machine translation (SimulMT) presents a challenging trade-off between translation quality and latency. Recent studies have shown that LLMs can achieve good performanc…

cs.CL2025

Simultaneous Machine Translation with Large Language Models

Minghan Wang, Jinming Zhao, Thuy-Trang Vu +3

Real-world simultaneous machine translation (SimulMT) systems face more challenges than just the quality-latency trade-off. They also need to address issues related to robustness w…

cs.CL2025

MAPLE: Multi-Agent Adaptive Planning with Long-Term Memory for Table Reasoning

Ye Bai, Minghan Wang, Thuy-Trang Vu

Table-based question answering requires complex reasoning capabilities that current LLMs struggle to achieve with single-pass inference. Existing approaches, such as Chain-of-Thoug…

cs.CL2025

Discourse Graph Guided Document Translation with Large Language Models

Viet-Thanh Pham, Minghan Wang, Hao-Han Liao +1

Adapting large language models to full document translation remains challenging due to the difficulty of capturing long-range dependencies and preserving discourse coherence throug…

cs.CL2025

Towards Inference-time Scaling for Continuous Space Reasoning

Minghan Wang, Thuy-Trang Vu, Ehsan Shareghi +1

Inference-time scaling through multiple sample generation in combination with Process- or Outcome-Reward Model (PRM or ORM) re-ranking has proven effective for text-based reasoning…

cs.CL2025

Discrete Minds in a Continuous World: Do Language Models Know Time Passes?

Minghan Wang, Ye Bai, Thuy-Trang Vu +2

While Large Language Models (LLMs) excel at temporal reasoning tasks like event ordering and duration estimation, their ability to perceive the actual passage of time remains unexp…