39 citations · 105 across the 12 of their papers we have counts for
12 papers
UrbanAlign: Post-hoc Semantic Calibration for VLM-Human Preference Alignment
Yecheng Zhang, Rong Zhao, Zhizhou Sha +10
Vision-language models (VLMs) can describe urban scenes in rich detail, yet consistently fail to produce reliable human preference labels in domain-specific tasks such as safety as…
Towards Cross-lingual Values Judgment: A Consensus-Pluralism Perspective
Yukun Chen, Xinyu Zhang, Boyi Deng +6
As large language models (LLMs) are employed worldwide, existing evaluation paradigms for their multilingual capabilities primarily focus on factual task performance, neglecting th…
PolyLM: An Open Source Polyglot Large Language Model
Xiangpeng Wei, Haoran Wei, Huan Lin +15
Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions. However, the development of LLMs has been pr…
Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors
Keqin Bao, Yu Wan, Dayiheng Liu +5
Fine-grained information on translation errors is helpful for the translation evaluation community. Existing approaches can not synchronously consider error position and type, fail…
Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task
Keqin Bao, Yu Wan, Dayiheng Liu +5
In this paper, we present our submission to the sentence-level MQM benchmark at Quality Estimation Shared Task, named UniTE (Unified Translation Evaluation). Specifically, our syst…
Alibaba-Translate China's Submission for WMT 2022 Metrics Shared Task
Yu Wan, Keqin Bao, Dayiheng Liu +5
In this report, we present our submission to the WMT 2022 Metrics Shared Task. We build our system based on the core idea of UNITE (Unified Translation Evaluation), which unifies s…
Attention Mechanism with Energy-Friendly Operations
Yu Wan, Baosong Yang, Dayiheng Liu +5
Attention mechanism has become the dominant module in natural language processing models. It is computationally intensive and depends on massive power-hungry multiplications. In th…
RoBLEURT Submission for the WMT2021 Metrics Task
Yu Wan, Dayiheng Liu, Baosong Yang +6
In this paper, we present our submission to Shared Metrics Task: RoBLEURT (Robustly Optimizing the training of BLEURT). After investigating the recent advances of trainable metrics…
UniTE: Unified Translation Evaluation
Yu Wan, Dayiheng Liu, Baosong Yang +4
Translation quality evaluation plays a crucial role in machine translation. According to the input format, it is mainly separated into three tasks, i.e., reference-only, source-onl…
RMBR: A Regularized Minimum Bayes Risk Reranking Framework for Machine Translation
Yidan Zhang, Yu Wan, Dayiheng Liu +2
Beam search is the most widely used decoding method for neural machine translation (NMT). In practice, the top-1 candidate with the highest log-probability among the n candidates i…
Self-Paced Learning for Neural Machine Translation
Yu Wan, Baosong Yang, Derek F. Wong +4
Recent studies have proven that the training of neural machine translation (NMT) can be facilitated by mimicking the learning process of humans. Nevertheless, achievements of such…
Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling
Yu Wan, Baosong Yang, Derek F. Wong +3
As a special machine translation task, dialect translation has two main characteristics: 1) lack of parallel training corpus; and 2) possessing similar grammar between two sides of…