Search Results for author: Kaiyu Huang

Found 17 papers, 8 papers with code

Lexicon-Based Graph Convolutional Network for Chinese Word Segmentation

no code implementations Findings (EMNLP) 2021 Kaiyu Huang, Hao Yu, Junpeng Liu, Wei Liu, Jingxiang Cao, Degen Huang

Experimental results on five benchmarks and four cross-domain datasets show the lexicon-based graph convolutional network successfully captures the information of candidate words and helps to improve performance on the benchmarks (Bakeoff-2005 and CTB6) and the cross-domain datasets (SIGHAN-2010).

Chinese Word Segmentation

Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models

no code implementations10 Jan 2025 You Li, Heyu Huang, Chi Chen, Kaiyu Huang, Chao Huang, Zonghao Guo, Zhiyuan Liu, Jinan Xu, Yuhua Li, Ruixuan Li, Maosong Sun

The recent advancement of Multimodal Large Language Models (MLLMs) has significantly improved their fine-grained perception of single images and general comprehension across multiple images.

Image Comprehension Instruction Following

Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search

1 code implementation29 Jul 2024 Fengran Mo, Chen Qu, Kelong Mao, Yihong Wu, Zhan Su, Kaiyu Huang, Jian-Yun Nie

In this paper, we leverage both rewritten queries and relevance judgments in the conversational search data to train a better query representation model.

Conversational Search

How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrieval

1 code implementation23 Jul 2024 Fengran Mo, Longxiang Zhao, Kaiyu Huang, Yue Dong, Degen Huang, Jian-Yun Nie

Personalized conversational information retrieval (CIR) combines conversational and personalizable elements to satisfy various users' complex information needs through multi-turn interaction based on their backgrounds.

Information Retrieval Language Modeling +3

A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers

1 code implementation17 May 2024 Kaiyu Huang, Fengran Mo, Xinyu Zhang, Hongliang Li, You Li, Yuanchi Zhang, Weijian Yi, Yulong Mao, Jinchen Liu, Yuzhuang Xu, Jinan Xu, Jian-Yun Nie, Yang Liu

The survey aims to help the research community address multilingual problems and provide a comprehensive understanding of the core concepts, key techniques, and latest developments in multilingual natural language processing based on LLMs.

Information Retrieval Survey

ConvSDG: Session Data Generation for Conversational Search

1 code implementation17 Mar 2024 Fengran Mo, Bole Yi, Kelong Mao, Chen Qu, Kaiyu Huang, Jian-Yun Nie

Conversational search provides a more convenient interface for users to search by allowing multi-turn interaction with the search engine.

Conversational Search Retrieval +1

Improving Cross-lingual Representation for Semantic Retrieval with Code-switching

no code implementations3 Mar 2024 Mieradilijiang Maimaiti, Yuanhang Zheng, Ji Zhang, Fei Huang, Yue Zhang, Wenpei Luo, Kaiyu Huang

Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario.

Question Answering Retrieval +3

History-Aware Conversational Dense Retrieval

1 code implementation30 Jan 2024 Fengran Mo, Chen Qu, Kelong Mao, Tianyu Zhu, Zhan Su, Kaiyu Huang, Jian-Yun Nie

To address the aforementioned issues, we propose a History-Aware Conversational Dense Retrieval (HAConvDR) system, which incorporates two ideas: context-denoised query reformulation and automatic mining of supervision signals based on the actual impact of historical turns.

Conversational Search Information Retrieval +1

ConvGQR: Generative Query Reformulation for Conversational Search

1 code implementation25 May 2023 Fengran Mo, Kelong Mao, Yutao Zhu, Yihong Wu, Kaiyu Huang, Jian-Yun Nie

In this paper, we propose ConvGQR, a new framework to reformulate conversational queries based on generative pre-trained language models (PLMs), one for query rewriting and another for generating potential answers.

Conversational Search Retrieval

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