activity
20242026
most citedNoRA: Nested Low-Rank Adaptation for Efficient Fine-Tuning Large Models

2 citations · 7 across the 30 of their papers we have counts for

collaborators

30 papers

cs.LG2026

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning

Evan Ning, Wei Xue, Dong Lou +1

Weight-space regularization methods such as Elastic Weight Consolidation (EWC) are the standard approach to catastrophic forgetting in continual learning. However, those methods te…

eess.AS2026

SqueezeComposer: Temporal Speed-up is A Simple Trick for Long-form Music Composing

Jianyi Chen, Rongxiu Zhong, Shilei Zhang +4

Composing coherent long-form music remains a significant challenge due to the complexity of modeling long-range dependencies and the prohibitive memory and computational requiremen…

cs.CV2026

DreamVideo-Omni: Omni-Motion Controlled Multi-Subject Video Customization with Latent Identity Reinforcement Learning

Yujie Wei, Xinyu Liu, Shiwei Zhang +12

While large-scale diffusion models have revolutionized video synthesis, achieving precise control over both multi-subject identity and multi-granularity motion remains a significan…

cs.CV2026

Data-Efficient Brushstroke Generation with Diffusion Models for Oil Painting

Dantong Qin, Alessandro Bozzon, Xian Yang +3

Many creative multimedia systems are built upon visual primitives such as strokes or textures, which are difficult to collect at scale and fundamentally different from natural imag…

cs.CV2026

UniSH: Unifying Scene and Human Reconstruction in a Feed-Forward Pass

Mengfei Li, Peng Li, Zheng Zhang +9

We present UniSH, a unified, feed-forward framework for joint metric-scale 3D scene and human reconstruction. A key challenge in this domain is the scarcity of large-scale, annotat…

cs.CV2025

CogniEdit: Dense Gradient Flow Optimization for Fine-Grained Image Editing

Yan Li, Lin Liu, Xiaopeng Zhang +4

Instruction-based image editing with diffusion models has achieved impressive results, yet existing methods struggle with fine-grained instructions specifying precise attributes su…

cs.CV2025

Towards Reason-Informed Video Editing in Unified Models with Self-Reflective Learning

Xinyu Liu, Hangjie Yuan, Yujie Wei +9

Unified video models exhibit strong capabilities in understanding and generation, yet they struggle with reason-informed visual editing even when equipped with powerful internal vi…

cs.CV2025

Scale-Aware Curriculum Learning for Ddata-Efficient Lung Nodule Detection with YOLOv11

Yi Luo, Yike Guo, Hamed Hooshangnejad +1

Lung nodule detection in chest CT is crucial for early lung cancer diagnosis, yet existing deep learning approaches face challenges when deployed in clinical settings with limited…

cs.RO2025

WoW: Towards a World omniscient World model Through Embodied Interaction

Xiaowei Chi, Peidong Jia, Chun-Kai Fan +33

Humans develop an understanding of intuitive physics through active interaction with the world. This approach is in stark contrast to current video models, such as Sora, which rely…

cs.CV2025

PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image

Peng Li, Yisheng He, Yingdong Hu +8

We present a feed-forward framework for static Gaussian full-head reconstruction and novel-view rendering from a single unposed image. Unlike previous work that relies on time-cons…

cs.SD2025

UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice

Sitong Cheng, Weizhen Bian, Xinsheng Wang +5

The ultimate goal of expressive speech-to-speech translation (S2ST) is to accurately translate spoken content while preserving the speaker identity and emotional style. However, pr…

cs.CL2025

Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks

Chunyang Jiang, Yonggang Zhang, Yiyang Cai +5

The rising cost of acquiring supervised data has driven significant interest in self-improvement for large language models (LLMs). Straightforward unsupervised signals like majorit…

cs.SD2025

Inference-time Scaling for Diffusion-based Audio Super-resolution

Yizhu Jin, Zhen Ye, Zeyue Tian +4

Diffusion models have demonstrated remarkable success in generative tasks, including audio super-resolution (SR). In many applications like movie post-production and album masterin…

cs.CV2025

CoGesture: Towards Coherent Concurrent Co-speech 3D Gesture Generation with Interactive Diffusion

Xingqun Qi, Yatian Wang, Hengyuan Zhang +6

Generating gestures from human speech has gained tremendous progress in animating virtual avatars. While the existing methods enable synthesizing gestures cooperated by individual…

cs.CL2025

Graceful Forgetting in Generative Language Models

Chunyang Jiang, Chi-min Chan, Yiyang Cai +3

Recently, the pretrain-finetune paradigm has become a cornerstone in various deep learning areas. While in general the pre-trained model would promote both effectiveness and effici…

cs.CV2025

CMD: Controllable Multiview Diffusion for 3D Editing and Progressive Generation

Peng Li, Suizhi Ma, Jialiang Chen +7

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to…

cs.CV2025★ 1 cited

VFX Creator: Animated Visual Effect Generation with Controllable Diffusion Transformer

Xinyu Liu, Ailing Zeng, Wei Xue +4

Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual effects (VFX) serving as the powerhouse behind unforgettable cinematic experiences. Whi…

cs.MM2025

AudioX: A Unified Framework for Anything-to-Audio Generation

Zeyue Tian, Zhaoyang Liu, Yizhu Jin +6

Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…

eess.AS2025★ 1 cited

YuE: Scaling Open Foundation Models for Long-Form Music Generation

Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55

We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…

cs.LG2025★ 1 cited

Delta Decompression for MoE-based LLMs Compression

Hao Gu, Wei Li, Lujun Li +5

Mixture-of-Experts (MoE) architectures in large language models (LLMs) achieve exceptional performance, but face prohibitive storage and memory requirements. To address these chall…

eess.AS2025

Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis

Zhen Ye, Xinfa Zhu, Chi-Min Chan +17

Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…

cs.CV2025

Every Angle Is Worth A Second Glance: Mining Kinematic Skeletal Structures from Multi-view Joint Cloud

Junkun Jiang, Jie Chen, Ho Yin Au +3

Multi-person motion capture over sparse angular observations is a challenging problem under interference from both self- and mutual-occlusions. Existing works produce accurate 2D j…

cs.CV2024

SINGER: Vivid Audio-driven Singing Video Generation with Multi-scale Spectral Diffusion Model

Yan Li, Ziya Zhou, Zhiqiang Wang +3

Recent advancements in generative models have significantly enhanced talking face video generation, yet singing video generation remains underexplored. The differences between huma…

cs.CV2024★ 1 cited

Foundation Cures Personalization: Improving Personalized Models' Prompt Consistency via Hidden Foundation Knowledge

Yiyang Cai, Zhengkai Jiang, Yulong Liu +4

Facial personalization faces challenges to maintain identity fidelity without disrupting the foundation model's prompt consistency. The mainstream personalization models employ ide…