5 papers
Finding the Translation Switch: Discovering and Exploiting the Task-Initiation Features in LLMs
Xinwei Wu, Heng Liu, Xiaohu Zhao +6
Large Language Models (LLMs) frequently exhibit strong translation abilities, even without task-specific fine-tuning. However, the internal mechanisms governing this innate capabil…
Challenging Multilingual LLMs: A New Taxonomy and Benchmark for Unraveling Hallucination in Translation
Xinwei Wu, Heng Liu, Jiang Zhou +5
Large Language Models (LLMs) have advanced machine translation but remain vulnerable to hallucinations. Unfortunately, existing MT benchmarks are not capable of exposing failures i…
: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation
Hao Wang, Linlong Xu, Heng Liu +12
Aligning Large Language Models (LLMs) with human preferences is pivotal for Machine Translation (MT), yet current approaches are often hindered by misleading reward signals. Our an…
Rethinking Multilingual Vision-Language Translation: Dataset, Evaluation, and Adaptation
Xintong Wang, Jingheng Pan, Yixiao Liu +8
Vision-Language Translation (VLT) is a challenging task that requires accurately recognizing multilingual text embedded in images and translating it into the target language with t…
Marco-LLM: Bridging Languages via Massive Multilingual Training for Cross-Lingual Enhancement
Lingfeng Ming, Bo Zeng, Chenyang Lyu +17
Large Language Models (LLMs) have achieved remarkable progress in recent years; however, their excellent performance is still largely limited to major world languages, primarily En…