16 citations · 41 across the 22 of their papers we have counts for
18 papers · 1 filter
AgentCTG: Harnessing Multi-Agent Collaboration for Fine-Grained Precise Control in Text Generation
Xinxu Zhou, Jiaqi Bai, Zhenqi Sun +2
Although significant progress has been made in many tasks within the field of Natural Language Processing (NLP), Controlled Text Generation (CTG) continues to face numerous challen…
Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow
Jiaqi Bai, Hongcheng Guo, Zhongyuan Peng +4
Large vision-language models show tremendous potential in understanding visual information through human languages. However, they are prone to suffer from object hallucination, i.e…
Towards Real-world Scenario: Imbalanced New Intent Discovery
Shun Zhang, Chaoran Yan, Jian Yang +5
New Intent Discovery (NID) aims at detecting known and previously undefined categories of user intent by utilizing limited labeled and massive unlabeled data. Most prior works ofte…
RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations
Shun Zhang, Chaoran Yan, Jian Yang +4
New Intent Discovery (NID) strives to identify known and reasonably deduce novel intent groups in the open-world scenario. But current methods face issues with inaccurate pseudo-la…
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt
Jian Yang, Hongcheng Guo, Yuwei Yin +7
Multilingual translation supports multiple translation directions by projecting all languages in a shared space, but the translation quality is undermined by the difference between…
New Intent Discovery with Attracting and Dispersing Prototype
Shun Zhang, Jian Yang, Jiaqi Bai +4
New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data. The task is addressed as a featu…
xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning
Linzheng Chai, Jian Yang, Tao Sun +8
Chain-of-thought (CoT) has emerged as a powerful technique to elicit reasoning in large language models and improve a variety of downstream tasks. CoT mainly demonstrates excellent…
MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL
Bing Wang, Changyu Ren, Jian Yang +8
Recent LLM-based Text-to-SQL methods usually suffer from significant performance degradation on "huge" databases and complex user questions that require multi-step reasoning. Moreo…
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…
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…
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…
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…
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…
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…
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…
Jointly Learning to Repair Code and Generate Commit Message
Jiaqi Bai, Long Zhou, Ambrosio Blanco +4
We propose a novel task of jointly repairing program codes and generating commit messages. Code repair and commit message generation are two essential and related tasks for softwar…
StyleDGPT: Stylized Response Generation with Pre-trained Language Models
Ze Yang, Wei Wu, Can Xu +5
Generating responses following a desired style has great potentials to extend applications of open-domain dialogue systems, yet is refrained by lacking of parallel data for trainin…