9 citations · 48 across the 36 of their papers we have counts for
37 papers
Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast
Jiaxin Guo, Yanwei Yue, Xuanbo Fan +2
On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a powerful information asymmetr…
The GaoYao Benchmark: A Comprehensive Framework for Evaluating Multilingual and Multicultural Abilities of Large Language Models
Yilun Liu, Chunguang Zhao, Mengyao Piao +14
Evaluating the multilingual and multicultural capabilities of Large Language Models (LLMs) is essential for their global utility. However, current benchmarks face three critical li…
Memory in the Age of AI Agents
Yuyang Hu, Shichun Liu, Yanwei Yue +44
Memory has emerged, and will continue to remain, a core capability of foundation model-based agents. As research on agent memory rapidly expands and attracts unprecedented attentio…
Mem-T: Densifying Rewards for Long-Horizon Memory Agents
Yanwei Yue, Boci Peng, Xuanbo Fan +3
Memory agents, which depart from predefined memory-processing pipelines by endogenously managing the processing, storage, and retrieval of memories, have garnered increasing attent…
DINO-Tok: Adapting DINO for Visual Tokenizers
Mingkai Jia, Mingxiao Li, Zhijian Shu +12
Recent advances in visual generation have emphasized the importance of Latent Generative Models (LGMs), which critically depend on effective visual tokenizers to bridge pixels and…
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
Yuezhou Hu, Jiaxin Guo, Xinyu Feng +1
Speculative Decoding (SD) accelerates large language model inference by employing a small draft model to generate predictions, which are then verified by a larger target model. The…
Align-then-Slide: A complete evaluation framework for Ultra-Long Document-Level Machine Translation
Jiaxin Guo, Daimeng Wei, Yuanchang Luo +8
Large language models (LLMs) have ushered in a new era for document-level machine translation (\textit{doc}-mt), yet their whole-document outputs challenge existing evaluation meth…
Generative Annotation for ASR Named Entity Correction
Yuanchang Luo, Daimeng Wei, Shaojun Li +8
End-to-end automatic speech recognition systems often fail to transcribe domain-specific named entities, causing catastrophic failures in downstream tasks. Numerous fast and lightw…
MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization
Mingkai Jia, Wei Yin, Xiaotao Hu +5
Vector Quantized Variational Autoencoders (VQ-VAEs) are fundamental models that compress continuous visual data into discrete tokens. Existing methods have tried to improve the qua…
Reward Reasoning Model
Jiaxin Guo, Zewen Chi, Li Dong +4
Reward models play a critical role in guiding large language models toward outputs that align with human expectations. However, an open challenge remains in effectively utilizing t…
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
Zhanglin Wu, Daimeng Wei, Xiaoyu Chen +7
Large language model (LLM) shows promising performances in a variety of downstream tasks, such as machine translation (MT). However, using LLMs for translation suffers from high co…
Automatic Evaluation Metrics for Document-level Translation: Overview, Challenges and Trends
Jiaxin GUO, Xiaoyu Chen, Zhiqiang Rao +5
With the rapid development of deep learning technologies, the field of machine translation has witnessed significant progress, especially with the advent of large language models (…
Chain-of-Description: What I can understand, I can put into words
Jiaxin Guo, Daimeng Wei, Zongyao Li +3
In this paper, we propose a novel strategy defined as Chain-of-Description (CoD) Prompting, tailored for Multi-Modal Large Language Models. This approach involves having the model…
DEUCE: Dual-diversity Enhancement and Uncertainty-awareness for Cold-start Active Learning
Jiaxin Guo, C. L. Philip Chen, Shuzhen Li +1
Cold-start active learning (CSAL) selects valuable instances from an unlabeled dataset for manual annotation. It provides high-quality data at a low annotation cost for label-scarc…
Doc-Guided Sent2Sent++: A Sent2Sent++ Agent with Doc-Guided memory for Document-level Machine Translation
Jiaxin Guo, Yuanchang Luo, Daimeng Wei +8
The field of artificial intelligence has witnessed significant advancements in natural language processing, largely attributed to the capabilities of Large Language Models (LLMs).…
M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models
Jiaxin Guo, Daimeng Wei, Yuanchang Luo +8
With the widespread application of Large Language Models (LLMs) in the field of Natural Language Processing (NLP), enhancing their performance has become a research hotspot. This p…
HW-TSC's Submission to the CCMT 2024 Machine Translation Tasks
Zhanglin Wu, Yuanchang Luo, Daimeng Wei +9
This paper presents the submission of Huawei Translation Services Center (HW-TSC) to machine translation tasks of the 20th China Conference on Machine Translation (CCMT 2024). We p…
Context-aware and Style-related Incremental Decoding framework for Discourse-Level Literary Translation
Yuanchang Luo, Jiaxin Guo, Daimeng Wei +7
This report outlines our approach for the WMT24 Discourse-Level Literary Translation Task, focusing on the Chinese-English language pair in the Constrained Track. Translating liter…
Multilingual Transfer and Domain Adaptation for Low-Resource Languages of Spain
Yuanchang Luo, Zhanglin Wu, Daimeng Wei +9
This article introduces the submission status of the Translation into Low-Resource Languages of Spain task at (WMT 2024) by Huawei Translation Service Center (HW-TSC). We participa…
Exploring the traditional NMT model and Large Language Model for chat translation
Jinlong Yang, Hengchao Shang, Daimeng Wei +10
This paper describes the submissions of Huawei Translation Services Center(HW-TSC) to WMT24 chat translation shared task on EnglishGermany (en-de) bidirection. The…
Machine Translation Advancements of Low-Resource Indian Languages by Transfer Learning
Bin Wei, Jiawei Zhen, Zongyao Li +10
This paper introduces the submission by Huawei Translation Center (HW-TSC) to the WMT24 Indian Languages Machine Translation (MT) Shared Task. To develop a reliable machine transla…
Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Task
Zhanglin Wu, Daimeng Wei, Zongyao Li +7
This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT24 general machine translation (MT) shared task, where we participate in the English to Ch…
LA-RAG:Enhancing LLM-based ASR Accuracy with Retrieval-Augmented Generation
Shaojun Li, Hengchao Shang, Daimeng Wei +5
Recent advancements in integrating speech information into large language models (LLMs) have significantly improved automatic speech recognition (ASR) accuracy. However, existing m…
An End-to-End Speech Summarization Using Large Language Model
Hengchao Shang, Zongyao Li, Jiaxin Guo +5
Abstractive Speech Summarization (SSum) aims to generate human-like text summaries from spoken content. It encounters difficulties in handling long speech input and capturing the i…