19 citations · 46 across the 60 of their papers we have counts for
60 papers
ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification
Jianzong Wang, Chuhang Liu, Botao Zhao +6
Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions remains a major obstacle to…
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Unified Multimodal models (UMMs) built on a single architecture have shown impressive performance in both understanding and generation. We identify a fundamental challenge that lie…
Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization
Jianzong Wang, Botao Zhao, Yayun He +2
Achieving general-purpose robotics requires empowering robots to adapt and evolve based on their environment and feedback. Traditional methods face limitations such as extensive tr…
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration
Jiaqi Shi, Yuechan Li, Xulong Zhang +2
High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Existing acceleration strategi…
Attention-weighted Centered Kernel Alignment for Knowledge Distillation in Large Audio-Language Models Applied to Speech Emotion Recognition
Qingran Yang, Botao Zhao, Zuheng Kang +7
The emergence of Large Audio-Language Models (LALMs) has advanced Speech Emotion Recognition (SER), but their size limits deployment in resource-constrained environments. While Kno…
MIRRORTALK: Forging Personalized Avatars Via Disentangled Style and Hierarchical Motion Control
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Synthesizing personalized talking faces that uphold and highlight a speaker's unique style while maintaining lip-sync accuracy remains a significant challenge. A primary limitation…
CARE: Multi-Task Pretraining for Latent Continuous Action Representation in Robot Control
Jiaqi Shi, Xulong Zhang, Xiaoyang Qu +1
Recent advances in Vision-Language-Action (VLA) models have shown promise for robot control, but their dependence on action supervision limits scalability and generalization. To ad…
CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Ziqi Liang, Xulong Zhang, Chang Liu +3
Voice Conversion (VC) aims to convert the style of a source speaker, such as timbre and pitch, to the style of any target speaker while preserving the linguistic content. However,…
ESARM: 3D Emotional Speech-to-Animation via Reward Model from Automatically-Ranked Demonstrations
Xulong Zhang, Xiaoyang Qu, Haoxiang Shi +2
This paper proposes a novel 3D speech-to-animation (STA) generation framework designed to address the shortcomings of existing models in producing diverse and emotionally resonant…
IDEAW: Robust Neural Audio Watermarking with Invertible Dual-Embedding
Pengcheng Li, Xulong Zhang, Jing Xiao +1
The audio watermarking technique embeds messages into audio and accurately extracts messages from the watermarked audio. Traditional methods develop algorithms based on expert expe…
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning
Haoxiang Shi, Xulong Zhang, Ning Cheng +4
The purpose of emotion recognition in conversation (ERC) is to identify the emotion category of an utterance based on contextual information. Previous ERC methods relied on simple…
RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Jianzong Wang, Haoxiang Shi, Kaiyi Luo +3
Known for efficient computation and easy storage, hashing has been extensively explored in cross-modal retrieval. The majority of current hashing models are predicated on the premi…
RSET: Remapping-based Sorting Method for Emotion Transfer Speech Synthesis
Haoxiang Shi, Jianzong Wang, Xulong Zhang +3
Although current Text-To-Speech (TTS) models are able to generate high-quality speech samples, there are still challenges in developing emotion intensity controllable TTS. Most exi…
MAIN-VC: Lightweight Speech Representation Disentanglement for One-shot Voice Conversion
Pengcheng Li, Jianzong Wang, Xulong Zhang +3
One-shot voice conversion aims to change the timbre of any source speech to match that of the unseen target speaker with only one speech sample. Existing methods face difficulties…
Learning Expressive Disentangled Speech Representations with Soft Speech Units and Adversarial Style Augmentation
Yimin Deng, Jianzong Wang, Xulong Zhang +2
Voice conversion is the task to transform voice characteristics of source speech while preserving content information. Nowadays, self-supervised representation learning models are…
QLSC: A Query Latent Semantic Calibrator for Robust Extractive Question Answering
Sheng Ouyang, Jianzong Wang, Yong Zhang +5
Extractive Question Answering (EQA) in Machine Reading Comprehension (MRC) often faces the challenge of dealing with semantically identical but format-variant inputs. Our work intr…
EfficientASR: Speech Recognition Network Compression via Attention Redundancy and Chunk-Level FFN Optimization
Jianzong Wang, Ziqi Liang, Xulong Zhang +2
In recent years, Transformer networks have shown remarkable performance in speech recognition tasks. However, their deployment poses challenges due to high computational and storag…
EAD-VC: Enhancing Speech Auto-Disentanglement for Voice Conversion with IFUB Estimator and Joint Text-Guided Consistent Learning
Ziqi Liang, Jianzong Wang, Xulong Zhang +3
Using unsupervised learning to disentangle speech into content, rhythm, pitch, and timbre for voice conversion has become a hot research topic. Existing works generally take into a…
CONTUNER: Singing Voice Beautifying with Pitch and Expressiveness Condition
Jianzong Wang, Pengcheng Li, Xulong Zhang +2
Singing voice beautifying is a novel task that has application value in people's daily life, aiming to correct the pitch of the singing voice and improve the expressiveness without…
Medical Speech Symptoms Classification via Disentangled Representation
Jianzong Wang, Pengcheng Li, Xulong Zhang +2
Intent is defined for understanding spoken language in existing works. Both textual features and acoustic features involved in medical speech contain intent, which is important for…
Learning Disentangled Speech Representations with Contrastive Learning and Time-Invariant Retrieval
Yimin Deng, Huaizhen Tang, Xulong Zhang +3
Voice conversion refers to transferring speaker identity with well-preserved content. Better disentanglement of speech representations leads to better voice conversion. Recent stud…
ED-TTS: Multi-Scale Emotion Modeling using Cross-Domain Emotion Diarization for Emotional Speech Synthesis
Haobin Tang, Xulong Zhang, Ning Cheng +2
Existing emotional speech synthesis methods often utilize an utterance-level style embedding extracted from reference audio, neglecting the inherent multi-scale property of speech…
EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Model
Bingyuan Zhang, Xulong Zhang, Ning Cheng +3
In recent years, the field of talking faces generation has attracted considerable attention, with certain methods adept at generating virtual faces that convincingly imitate human…
CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embedding
Jianzong Wang, Yimin Deng, Ziqi Liang +3
This paper proposes a talking face generation method named "CP-EB" that takes an audio signal as input and a person image as reference, to synthesize a photo-realistic people talki…