2 citations · 5 across the 35 of their papers we have counts for
22 papers · 1 filter
Collaborative Representation Learning for Alignment of Tactile, Language, and Vision Modalities
Yiyun Zhou, Mingjing Xu, Jingwei Shi +2
Tactile sensing offers rich and complementary information to vision and language, enabling robots to perceive fine-grained object properties. However, existing tactile sensors lack…
From Noisy to Native: LLM-driven Graph Restoration for Test-Time Graph Domain Adaptation
Xiangwei Lv, JinLuan Yang, Wang Lin +2
Graph domain adaptation (GDA) has achieved great attention due to its effectiveness in addressing the domain shift between train and test data. A significant bottleneck in existing…
MARS-Sep: Multimodal-Aligned Reinforced Sound Separation
Zihan Zhang, Xize Cheng, Zhennan Jiang +4
Universal sound separation faces a fundamental misalignment: models optimized for low-level signal metrics often produce semantically contaminated outputs, failing to suppress perc…
Cognitive-Level Adaptive Generation via Capability-Aware Retrieval and Style Adaptation
Qingsong Wang, Tao Wu, Wang Lin +4
Large Language Models (LLMs) have demonstrated strong performance in open-ended generation tasks. However, they often struggle to adapt content to users with differing cognitive ca…
Tackling Device Data Distribution Real-time Shift via Prototype-based Parameter Editing
Zheqi Lv, Wenqiao Zhang, Kairui Fu +6
The on-device real-time data distribution shift on devices challenges the generalization of lightweight on-device models. This critical issue is often overlooked in current researc…
Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction
Tao Wu, Jingyuan Chen, Wang Lin +6
Distractors-incorrect yet plausible answer choices in multiple-choice questions (MCQs)-are vital in educational assessments, as they help identify student misconceptions by present…
Show and Polish: Reference-Guided Identity Preservation in Face Video Restoration
Wenkang Han, Wang Lin, Yiyun Zhou +4
Face Video Restoration (FVR) aims to recover high-quality face videos from degraded versions. Traditional methods struggle to preserve fine-grained, identity-specific features when…
Advancing Medical Image Segmentation via Self-supervised Instance-adaptive Prototype Learning
Guoyan Liang, Qin Zhou, Jingyuan Chen +2
Medical Image Segmentation (MIS) plays a crucial role in medical therapy planning and robot navigation. Prototype learning methods in MIS focus on generating segmentation masks thr…
Semantic-guided Masked Mutual Learning for Multi-modal Brain Tumor Segmentation with Arbitrary Missing Modalities
Guoyan Liang, Qin Zhou, Jingyuan Chen +6
Malignant brain tumors have become an aggressive and dangerous disease that leads to death worldwide.Multi-modal MRI data is crucial for accurate brain tumor segmentation, but miss…
Learnable Retrieval Enhanced Visual-Text Alignment and Fusion for Radiology Report Generation
Qin Zhou, Guoyan Liang, Xindi Li +4
Automated radiology report generation is essential for improving diagnostic efficiency and reducing the workload of medical professionals. However, existing methods face significan…
Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model Updating
Yiyun Zhou, Zheqi Lv, Shengyu Zhang +1
Knowledge Tracing (KT) is a core component of Intelligent Tutoring Systems, modeling learners' knowledge state to predict future performance and provide personalized learning suppo…
CoLA: Collaborative Low-Rank Adaptation
Yiyun Zhou, Chang Yao, Jingyuan Chen
The scaling law of Large Language Models (LLMs) reveals a power-law relationship, showing diminishing return on performance as model scale increases. While training LLMs from scrat…
Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer
Wenkang Han, Wang Lin, Liya Hu +6
Knowledge tracing (KT) aims to predict learners' future performance based on historical learning interactions. However, existing KT models predominantly focus on data from a single…
Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based Agents
Tao Wu, Jingyuan Chen, Wang Lin +5
Large language models (LLMs) are revolutionizing education, with LLM-based agents playing a key role in simulating student behavior. A major challenge in student simulation is mode…
Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning
Wang Lin, Liyu Jia, Wentao Hu +6
Despite recent progress in video generation, producing videos that adhere to physical laws remains a significant challenge. Traditional diffusion-based methods struggle to extrapol…
Code2API: A Tool for Generating Reusable APIs from Stack Overflow Code Snippets
Yubo Mai, Zhipeng Gao, Xing Hu +3
Nowadays, developers often turn to Stack Overflow for solutions to daily problems, however, these code snippets are partial code that cannot be tested and verified properly. One wa…
Towards Transformer-Based Aligned Generation with Self-Coherence Guidance
Shulei Wang, Wang Lin, Hai Huang +8
We introduce a novel, training-free approach for enhancing alignment in Transformer-based Text-Guided Diffusion Models (TGDMs). Existing TGDMs often struggle to generate semantical…
Disentangled Knowledge Tracing for Alleviating Cognitive Bias
Yiyun Zhou, Zheqi Lv, Shengyu Zhang +1
In the realm of Intelligent Tutoring System (ITS), the accurate assessment of students' knowledge states through Knowledge Tracing (KT) is crucial for personalized learning. Howeve…
Boosting MLLM Reasoning with Text-Debiased Hint-GRPO
Qihan Huang, Weilong Dai, Jinlong Liu +6
MLLM reasoning has drawn widespread research for its excellent problem-solving capability. Current reasoning methods fall into two types: PRM, which supervises the intermediate rea…
Knowledge is Power: Harnessing Large Language Models for Enhanced Cognitive Diagnosis
Zhiang Dong, Jingyuan Chen, Fei Wu
Cognitive Diagnosis Models (CDMs) are designed to assess students' cognitive states by analyzing their performance across a series of exercises. However, existing CDMs often strugg…
WisdomBot: Tuning Large Language Models with Artificial Intelligence Knowledge
Jingyuan Chen, Tao Wu, Wei Ji +1
Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite the…
DKT2: Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data
Yiyun Zhou, Wenkang Han, Jingyuan Chen
Knowledge Tracing (KT) is a fundamental component of Intelligent Tutoring Systems (ITS), enabling the modeling of students' knowledge states to predict future performance. The intr…