20 citations · 44 across the 37 of their papers we have counts for
42 papers
Beyond Pattern Matching in 3D MLLMs: Part-Level Functional Reasoning for Generalizable Recognition
Weihong Li, Hao Jiang, Yaohua Zha +2
3D MLLMs recognize objects via pattern matching, which fails when geometrically similar objects require functional reasoning to disambiguate (e.g., dresser vs. wardrobe). Our per-s…
DST-Net: Decomposed Spatio-Temporal Network for Time Series Forecasting
Yaohua Zha, Hai Wu, Shu-Tao Xia
Series decomposition has emerged as a widely acknowledged paradigm in deep time series forecasting models. However, existing approaches predominantly employ a homogeneous modeling…
W2Rep: Learning Visual Representations by Watching the World Change
Wen Huang, Hang Guo, Jiarui Yang +3
Images capture the world at one moment, whereas video reveals how it changes. Image self-supervision learns spatial structure from a single moment, while video methods commonly lea…
GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining
Jiarui Yang, Jiawei Li, Jiale Zhang +5
Latent action models (LAMs) learn action-related representations from action-free videos via self-supervised future prediction, offering a scalable paradigm for embodied intelligen…
UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents
Niu Lian, Tongbo Chen, Zhehao Yu +8
Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction. However, unified mul…
LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models
Jiarui Yang, Jiale Zhange, Jiawei Li +5
World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied intelligence remains limited by…
Beyond Illumination: A Conditional Mutual Information-Guided Network for Low-Light Image Enhancement
Ya-nan Guan, Shaonan Zhang, Tao Dai +5
Low-light image enhancement (LLIE) seeks to restore structural fidelity, natural color rendition, and proper exposure from images captured under inadequate lighting conditions. Rec…
ARBOR: Online Process Rewards via a Reusable Rubric Buffer for Search Agents
Zheng Liu, Longxiang Zhang, Xintong Wang +8
LLM-based search agents are trained predominantly with outcome-only reward, leaving the search process itself unsupervised. This signal degenerates on outcome-homogeneous groups wh…
Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting
Yixin Wang, Yifan Hu, Peiyuan Liu +3
Time series forecasting remains a challenging problem due to the intricate entanglement of intra-period fluctuations and inter-period trends. While recent advances have attempted t…
SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
Taolin Zhang, Hang Guo, Wang Lu +3
As large language models (LLMs) continue to scale up, their performance on various downstream tasks has significantly improved. However, evaluating their capabilities has become in…
CP Loss: Channel-wise Perceptual Loss for Time Series Forecasting
Yaohua Zha, Chunlin Fan, Peiyuan Liu +4
Multi-channel time-series data, prevalent across diverse applications, is characterized by significant heterogeneity in its different channels. However, existing forecasting models…
CASL: Curvature-Augmented Self-supervised Learning for 3D Anomaly Detection
Yaohua Zha, Xue Yuerong, Chunlin Fan +4
Deep learning-based 3D anomaly detection methods have demonstrated significant potential in industrial manufacturing. However, many approaches are specifically designed for anomaly…
JPRO: Automated Multimodal Jailbreaking via Multi-Agent Collaboration Framework
Yuxuan Zhou, Yang Bai, Kuofeng Gao +2
The widespread application of large VLMs makes ensuring their secure deployment critical. While recent studies have demonstrated jailbreak attacks on VLMs, existing approaches are…
Improving Deepfake Detection with Reinforcement Learning-Based Adaptive Data Augmentation
Yuxuan Zhou, Tao Yu, Wen Huang +3
The generalization capability of deepfake detectors is critical for real-world use. Data augmentation via synthetic fake face generation effectively enhances generalization, yet cu…
Why Does Weak-OOD Help? A Further Step Towards Understanding Jailbreaking VLMs
Yuxuan Zhou, Yuzhao Peng, Yang Bai +7
Large Vision-Language Models (VLMs) are susceptible to jailbreak attacks: researchers have developed various attack strategies that bypass the safety mechanisms of VLMs. Among thes…
Personalized Face Super-Resolution with Identity Decoupling and Fitting
Jiarui Yang, Hang Guo, Wen Huang +2
In recent years, face super-resolution (FSR) methods have achieved remarkable progress, generally maintaining high image fidelity and identity (ID) consistency under standard setti…
RelayFormer: A Unified Local-Global Attention Framework for Scalable Image and Video Manipulation Localization
Wen Huang, Jiarui Yang, Tao Dai +4
Visual manipulation localization (VML) aims to identify tampered regions in images and videos, a task that has become increasingly challenging with the rise of advanced editing too…
PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter
Yaohua Zha, Yanzi Wang, Hang Guo +7
Applying pre-trained models to assist point cloud understanding has recently become a mainstream paradigm in 3D perception. However, existing application strategies are straightfor…
Logic-of-Thought: Empowering Large Language Models with Logic Programs for Solving Puzzles in Natural Language
Naiqi Li, Peiyuan Liu, Zheng Liu +3
Solving puzzles in natural language poses a long-standing challenge in AI. While large language models (LLMs) have recently shown impressive capabilities in a variety of tasks, the…
Efficient Differentiable Approximation of Generalized Low-rank Regularization
Naiqi Li, Yuqiu Xie, Peiyuan Liu +3
Low-rank regularization (LRR) has been widely applied in various machine learning tasks, but the associated optimization is challenging. Directly optimizing the rank function under…
Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning
Jinpeng Wang, Tianci Luo, Yaohua Zha +7
Visual In-Context Learning (VICL) enables adaptively solving vision tasks by leveraging pixel demonstrations, mimicking human-like task completion through analogy. Prompt selection…
FastVAR: Linear Visual Autoregressive Modeling via Cached Token Pruning
Hang Guo, Yawei Li, Taolin Zhang +4
Visual Autoregressive (VAR) modeling has gained popularity for its shift towards next-scale prediction. However, existing VAR paradigms process the entire token map at each scale s…
FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
Yifan Hu, Yuante Li, Peiyuan Liu +6
Financial time series (FinTS) record the behavior of human-brain-augmented decision-making, capturing valuable historical information that can be leveraged for profitable investmen…
FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction
Yifan Hu, Peiyuan Liu, Yuante Li +5
Recently, combining stock features with inter-stock correlations has become a common and effective approach for stock movement prediction. However, financial data presents signific…