5 citations · 13 across the 34 of their papers we have counts for
36 papers
Mind the Couch! Eliciting MLLM Reasoning in Interior Design via Weak-to-Strong Task Vector Injection
Yuxuan Yang, Jingyao Wang, Luntian Mou
Multimodal Large Language Models (MLLMs) have demonstrated great performance, yet they often suffer from severe modality misalignment when confronted with densely constrained space…
Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting
Xingyu Zhang, Jingyao Wang, Xin Yu +4
Time series forecasting often suffers from over-smoothing, especially when future dynamics are multi-modal. Forecasts may follow the coarse trend of the observed future, but fail t…
GenPO++: Generative Policy Optimization with Jacobian-free Likelihood Ratios
Ke Hu, Shutong Ding, Panxin Tao +2
Generative policies provide expressive and multimodal action distributions, making them attractive for reinforcement learning (RL) in complex continuous-control tasks. Among them,…
CAMD: Coverage-Aware Multimodal Decoding for Efficient Reasoning of Multimodal Large Language Models
Huijie Guo, Jingyao Wang, Lingyu Si +3
Recent advances in Multimodal Large Language Models (MLLMs) have shown impressive reasoning capabilities across vision-language tasks, yet still face the challenge of compute-diffi…
Design-MLLM: A Reinforcement Alignment Framework for Verifiable and Aesthetic Interior Design
Yuxuan Yang, Xiaotong Mao, Jingyao Wang
Interior design is a requirements-to-visual-plan generation process that must simultaneously satisfy verifiable spatial feasibility and comparative aesthetic preferences. While rec…
On the Plasticity and Stability for Post-Training Large Language Models
Wenwen Qiang, Ziyin Gu, Jiahuan Zhou +4
Training stability remains a critical bottleneck for Group Relative Policy Optimization (GRPO), often manifesting as a trade-off between reasoning plasticity and general capability…
Towards Generalizable Reasoning: Group Causal Counterfactual Policy Optimization for LLM Reasoning
Jingyao Wang, Peizheng Guo, Wenwen Qiang +4
Large language models (LLMs) excel at complex tasks with advances in reasoning capabilities. However, existing reward mechanisms remain tightly coupled to final correctness and pay…
Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
Jianqi Zhang, Jingyao Wang, Wenwen Qiang +2
The World Wide Web needs reliable predictive capabilities to respond to changes in user behavior and usage patterns. Time series forecasting (TSF) is a key means to achieve this go…
Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration
Huijie Guo, Jingyao Wang, Peizheng Guo +3
In this paper, we explore the transferability of SSL by addressing two central questions: (i) what is the representation transferability of SSL, and (ii) how can we effectively mod…
A Generalized Learning Framework for Self-Supervised Contrastive Learning
Lingyu Si, Jingyao Wang, Wenwen Qiang
Self-supervised contrastive learning (SSCL) has recently demonstrated superiority in multiple downstream tasks. In this paper, we generalize the standard SSCL methods to a Generali…
Group Causal Policy Optimization for Post-Training Large Language Models
Ziyin Gu, Jingyao Wang, Ran Zuo +4
Recent advances in large language models (LLMs) have broadened their applicability across diverse tasks, yet specialized domains still require targeted post training. Among existin…
COPO: Causal-Oriented Policy Optimization for Hallucinations of MLLMs
Peizheng Guo, Jingyao Wang, Wenwen Qiang +3
Despite Multimodal Large Language Models (MLLMs) having shown impressive capabilities, they may suffer from hallucinations. Empirically, we find that MLLMs attend disproportionatel…
Advancing Complex Wide-Area Scene Understanding with Hierarchical Coresets Selection
Jingyao Wang, Yiming Chen, Lingyu Si +1
Scene understanding is one of the core tasks in computer vision, aiming to extract semantic information from images to identify objects, scene categories, and their interrelationsh…
On the Out-of-Distribution Generalization of Self-Supervised Learning
Wenwen Qiang, Jingyao Wang, Zeen Song +2
In this paper, we focus on the out-of-distribution (OOD) generalization of self-supervised learning (SSL). By analyzing the mini-batch construction during the SSL training phase, w…
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation
Jingyao Wang, Jianqi Zhang, Wenwen Qiang +1
Despite the strength of the Segment Anything Model (SAM), it struggles with generalization issues in open-vocabulary multi-entity segmentation (OVMS). Through empirical and causal…
Rethinking Multi-Modal Learning from Gradient Uncertainty
Peizheng Guo, Jingyao Wang, Wenwen Qiang +3
Multi-Modal Learning (MML) integrates information from diverse modalities to improve predictive accuracy. While existing optimization strategies have made significant strides by mi…
Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs
Jingyao Wang, Wenwen Qiang, Zeen Song +2
Large language models (LLMs) excel at complex tasks thanks to advances in their reasoning abilities. However, existing methods overlook the trade-off between reasoning effectivenes…
Fewer yet critical: Reducing Redundant Token Dependencies for Transformer-based Time Series Forecasting
Jianqi Zhang, Yuchan Liu, Zeen Song +2
Time series forecasting (TSF) is important in real-world applications. Recently, Transformer-based methods have achieved strong performance by modeling token dependencies through a…
Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion Recognition
Jingyao Wang, Wenwen Qiang, Changwen Zheng +1
Fine-grained emotion recognition (FER) plays a vital role in various fields, such as disease diagnosis, personalized recommendations, and multimedia mining. However, existing FER m…
Neuromodulated Meta-Learning
Jingyao Wang, Huijie Guo, Wenwen Qiang +4
Humans excel at adapting perceptions and actions to diverse environments, enabling efficient interaction with the external world. This adaptive capability relies on the biological…
DiffDesign: Controllable Diffusion with Meta Prior for Efficient Interior Design Generation
Yuxuan Yang, Tao Geng
Interior design is a complex and creative discipline involving aesthetics, functionality, ergonomics, and materials science. Effective solutions must meet diverse requirements, typ…
Less yet robust: crucial region selection for scene recognition
Jianqi Zhang, Mengxuan Wang, Jingyao Wang +3
Scene recognition, particularly for aerial and underwater images, often suffers from various types of degradation, such as blurring or overexposure. Previous works that focus on co…
Rethinking Meta-Learning from a Learning Lens
Jingyao Wang, Wenwen Qiang, Changwen Zheng +2
Meta-learning seeks to learn a well-generalized model initialization from training tasks to solve unseen tasks. From the "learning to learn" perspective, the quality of the initial…
Image-based Freeform Handwriting Authentication with Energy-oriented Self-Supervised Learning
Jingyao Wang, Luntian Mou, Changwen Zheng +1
Freeform handwriting authentication verifies a person's identity from their writing style and habits in messy handwriting data. This technique has gained widespread attention in re…