36 citations · 161 across the 34 of their papers we have counts for
34 papers
M2C: Towards Automatic Multimodal Manga Complement
Hongcheng Guo, Boyang Wang, Jiaqi Bai +3
Multimodal manga analysis focuses on enhancing manga understanding with visual and textual features, which has attracted considerable attention from both natural language processin…
Delving into Commit-Issue Correlation to Enhance Commit Message Generation Models
Liran Wang, Xunzhu Tang, Yichen He +4
Commit message generation (CMG) is a challenging task in automated software engineering that aims to generate natural language descriptions of code changes for commits. Previous me…
MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
Tongliang Li, Zixiang Wang, Linzheng Chai +8
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages. Previous work uses a shared cross-lingual pre-trained mode…
Unleashing Potential of Evidence in Knowledge-Intensive Dialogue Generation
Xianjie Wu, Jian Yang, Tongliang Li +4
Incorporating external knowledge into dialogue generation (KIDG) is crucial for improving the correctness of response, where evidence fragments serve as knowledgeable snippets supp…
OWL: A Large Language Model for IT Operations
Hongcheng Guo, Jian Yang, Jiaheng Liu +13
With the rapid development of IT operations, it has become increasingly crucial to efficiently manage and analyze large volumes of data for practical applications. The techniques o…
mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learning
Ying Mo, Jian Yang, Jiahao Liu +4
Cross-lingual named entity recognition (CrossNER) faces challenges stemming from uneven performance due to the scarcity of multilingual corpora, especially for non-English data. Wh…
KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation
Jiaqi Bai, Zhao Yan, Jian Yang +3
Existing knowledge-grounded conversation systems generate responses typically in a retrieve-then-generate manner. They require a large knowledge base and a strong knowledge retriev…
QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsing
Linzheng Chai, Dongling Xiao, Jian Yang +5
Context-dependent Text-to-SQL aims to translate multi-turn natural language questions into SQL queries. Despite various methods have exploited context-dependence information implic…
GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking
Jiaqi Bai, Hongcheng Guo, Jiaheng Liu +4
Retrieval-enhanced text generation has shown remarkable progress on knowledge-intensive language tasks, such as open-domain question answering and knowledge-enhanced dialogue gener…
Retrieval-Augmented Classification with Decoupled Representation
Xinnian Liang, Shuangzhi Wu, Hui Huang +3
Retrieval augmented methods have shown promising results in various classification tasks. However, existing methods focus on retrieving extra context to enrich the input, which is…
SCM: Enhancing Large Language Model with Self-Controlled Memory Framework
Bing Wang, Xinnian Liang, Jian Yang +6
Large Language Models (LLMs) are constrained by their inability to process lengthy inputs, resulting in the loss of critical historical information. To address this limitation, in…
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Minghao Li, Yingxiu Zhao, Bowen Yu +6
Recent research has demonstrated that Large Language Models (LLMs) can enhance their capabilities by utilizing external tools. However, three pivotal questions remain unanswered: (…
Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models
Xinnian Liang, Zefan Zhou, Hui Huang +5
Pretrained language models (PLMs) have shown marvelous improvements across various NLP tasks. Most Chinese PLMs simply treat an input text as a sequence of characters, and complete…
Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition
Ying Mo, Hongyin Tang, Jiahao Liu +5
Named entity recognition (NER) is an important research problem in natural language processing. There are three types of NER tasks, including flat, nested and discontinuous entity…
Enhancing Dialogue Summarization with Topic-Aware Global- and Local- Level Centrality
Xinnian Liang, Shuangzhi Wu, Chenhao Cui +3
Dialogue summarization aims to condense a given dialogue into a simple and focused summary text. Typically, both the roles' viewpoints and conversational topics change in the dialo…
HanoiT: Enhancing Context-aware Translation via Selective Context
Jian Yang, Yuwei Yin, Shuming Ma +7
Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or…
Multilingual Entity and Relation Extraction from Unified to Language-specific Training
Zixiang Wang, Jian Yang, Tongliang Li +5
Entity and relation extraction is a key task in information extraction, where the output can be used for downstream NLP tasks. Existing approaches for entity and relation extractio…
GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
Jian Yang, Shuming Ma, Li Dong +7
Pre-trained models have achieved remarkable success in natural language processing (NLP). However, existing pre-training methods underutilize the benefits of language understanding…
LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation
Hongcheng Guo, Jiaheng Liu, Haoyang Huang +5
Multimodal Machine Translation (MMT) focuses on enhancing text-only translation with visual features, which has attracted considerable attention from both natural language processi…
PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models
Yupeng Zhang, Hongzhi Zhang, Sirui Wang +2
A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs). However, a number of redundant parameters which contribute less to the downstream task…
CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translation
Jian Yang, Shaohan Huang, Shuming Ma +6
Named entity recognition (NER) suffers from the scarcity of annotated training data, especially for low-resource languages without labeled data. Cross-lingual NER has been proposed…
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +5
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enable…
An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks
Xinnian Liang, Jing Li, Shuangzhi Wu +4
Unsupervised summarization methods have achieved remarkable results by incorporating representations from pre-trained language models. However, existing methods fail to consider ef…
Modeling Paragraph-Level Vision-Language Semantic Alignment for Multi-Modal Summarization
Chenhao Cui, Xinnian Liang, Shuangzhi Wu +1
Most current multi-modal summarization methods follow a cascaded manner, where an off-the-shelf object detector is first used to extract visual features, then these features are fu…