4 citations · 11 across the 11 of their papers we have counts for
11 papers
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs
Zixuan Ren, Jinliang Lu, Junhong Wu +5
Model merging plays a crucial role in consolidating multiple specialized models into a single, unified model, especially in the era of large language models (LLMs). Recent research…
PromptDLA: A Domain-aware Prompt Document Layout Analysis Framework with Descriptive Knowledge as a Cue
Zirui Zhang, Yaping Zhang, Lu Xiang +4
Document Layout Analysis (DLA) is crucial for document artificial intelligence and has recently received increasing attention, resulting in an influx of large-scale public DLA data…
ICDAR 2025 Competition on End-to-End Document Image Machine Translation Towards Complex Layouts
Yaping Zhang, Yupu Liang, Zhiyang Zhang +5
Document Image Machine Translation (DIMT) seeks to translate text embedded in document images from one language to another by jointly modeling both textual content and page layout,…
HiSciBench: A Hierarchical Multi-disciplinary Benchmark for Scientific Intelligence from Reading to Discovery
Yaping Zhang, Qixuan Zhang, Xingquan Zhang +8
The rapid advancement of large language models (LLMs) and multimodal foundation models has sparked growing interest in their potential for scientific research. However, scientific…
A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities
Lu Xiang, Yang Zhao, Yaping Zhang +1
Large Language Models (LLMs) have demonstrated their transformative potential across numerous disciplinary studies, reshaping the existing research methodologies and fostering inte…
Improving MLLM's Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency
Yupu Liang, Yaping Zhang, Zhiyang Zhang +5
Multimodal Large Language Models (MLLMs) have shown strong performance in document image tasks, especially Optical Character Recognition (OCR). However, they struggle with Document…
Single-to-mix Modality Alignment with Multimodal Large Language Model for Document Image Machine Translation
Yupu Liang, Yaping Zhang, Zhiyang Zhang +4
Document Image Machine Translation (DIMT) aims to translate text within document images, facing generalization challenges due to limited training data and the complex interplay bet…
SimulPL: Aligning Human Preferences in Simultaneous Machine Translation
Donglei Yu, Yang Zhao, Jie Zhu +3
Simultaneous Machine Translation (SiMT) generates translations while receiving streaming source inputs. This requires the SiMT model to learn a read/write policy, deciding when to…
Boosting LLM Translation Skills without General Ability Loss via Rationale Distillation
Junhong Wu, Yang Zhao, Yangyifan Xu +2
Large Language Models (LLMs) have achieved impressive results across numerous NLP tasks but still encounter difficulties in machine translation. Traditional methods to improve tran…
Life-long Learning for Multilingual Neural Machine Translation with Knowledge Distillation
Yang Zhao, Junnan Zhu, Lu Xiang +4
A common scenario of Multilingual Neural Machine Translation (MNMT) is that each translation task arrives in a sequential manner, and the training data of previous tasks is unavail…
Dynamic Context Selection for Document-level Neural Machine Translation via Reinforcement Learning
Xiaomian Kang, Yang Zhao, Jiajun Zhang +1
Document-level neural machine translation has yielded attractive improvements. However, majority of existing methods roughly use all context sentences in a fixed scope. They neglec…