7 citations · 8 across the 7 of their papers we have counts for
8 papers
Cross-Granularity Hypergraph Retrieval-Augmented Generation for Multi-hop Question Answering
Changjian Wang, Weihong Deng, Weili Guan +2
Multi-hop question answering (MHQA) requires integrating knowledge scattered across multiple passages to derive the correct answer. Traditional retrieval-augmented generation (RAG)…
Referring Expression Instance Retrieval and A Strong End-to-End Baseline
Xiangzhao Hao, Kuan Zhu, Hongyu Guo +5
Using natural language to query visual information is a fundamental need in real-world applications. Text-Image Retrieval (TIR) retrieves a target image from a gallery based on an…
MiniCPM4: Ultra-Efficient LLMs on End Devices
MiniCPM Team, Chaojun Xiao, Yuxuan Li +80
This paper introduces MiniCPM4, a highly efficient large language model (LLM) designed explicitly for end-side devices. We achieve this efficiency through systematic innovation in…
Whisper-SV: Adapting Whisper for Low-data-resource Speaker Verification
Li Zhang, Ning Jiang, Qing Wang +3
Trained on 680,000 hours of massive speech data, Whisper is a multitasking, multilingual speech foundation model demonstrating superior performance in automatic speech recognition,…
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation
Zhigang Chen, Benjia Zhou, Jun Li +5
Previous Sign Language Translation (SLT) methods achieve superior performance by relying on gloss annotations. However, labeling high-quality glosses is a labor-intensive task, whi…
An audio-quality-based multi-strategy approach for target speaker extraction in the MISP 2023 Challenge
Runduo Han, Xiaopeng Yan, Weiming Xu +6
This paper describes our audio-quality-based multi-strategy approach for the audio-visual target speaker extraction (AVTSE) task in the Multi-modal Information based Speech Process…
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features
Tianshun Han, Shengnan Gui, Yiqing Huang +9
Speech-driven 3D facial animation has improved a lot recently while most related works only utilize acoustic modality and neglect the influence of visual and textual cues, leading…
Conversational Speech Recognition by Learning Audio-textual Cross-modal Contextual Representation
Kun Wei, Bei Li, Hang Lv +3
Automatic Speech Recognition (ASR) in conversational settings presents unique challenges, including extracting relevant contextual information from previous conversational turns. D…