2 citations · 2 across the 10 of their papers we have counts for
10 papers
Learn from Whoever Is Right: Answer-Verified Multi-Teacher Distillation for Multi-Domain LLMs
Xixiang He, Xingming Li, Baiqi Wu +4
Modern large language models (LLMs) rely on reinforcement learning to build strong capabilities in individual domains, but integrating those capabilities into a single deployable m…
Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation
Xixiang He, Qiyao Sun, Ao Cheng +5
Group Relative Policy Optimization (GRPO), a prominent algorithm within the Reinforcement Learning from Verifiable Rewards (RLVR) framework, has achieved strong results in improvin…
StemBind: When MLLMs Get Lost Between Rules and Instances in Abstract Visual Reasoning
Xixiang He, Baiqi Wu, Xingming Li +4
Multimodal large language models (MLLMs) often know the rule but pick the wrong answer: on abstract visual reasoning (AVR) tasks, a model can describe what it sees and name the und…
When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools
Xingming Li, Runke Huang, Yanan Bao +3
High-quality teacher-child interaction (TCI) is fundamental to early childhood development, yet traditional expert-based assessment faces a critical scalability challenge. In large…
Efficient Hallucination Detection: Adaptive Bayesian Estimation of Semantic Entropy with Guided Semantic Exploration
Qiyao Sun, Xingming Li, Xixiang He +5
Large language models (LLMs) have achieved remarkable success in various natural language processing tasks, yet they remain prone to generating factually incorrect outputs known as…
ENC-Bench: A Benchmark for Evaluating Multimodal Large Language Models in Electronic Navigational Chart Understanding
Ao Cheng, Xingming Li, Xuanyu Ji +5
Electronic Navigational Charts (ENCs) are the safety-critical backbone of modern maritime navigation, yet it remains unclear whether multimodal large language models (MLLMs) can re…
PhysDrive: A Multimodal Remote Physiological Measurement Dataset for In-vehicle Driver Monitoring
Jiyao Wang, Xiao Yang, Qingyong Hu +6
Robust and unobtrusive in-vehicle physiological monitoring is crucial for ensuring driving safety and user experience. While remote physiological measurement (RPM) offers a promisi…
Period-LLM: Extending the Periodic Capability of Multimodal Large Language Model
Yuting Zhang, Hao Lu, Qingyong Hu +4
Periodic or quasi-periodic phenomena reveal intrinsic characteristics in various natural processes, such as weather patterns, movement behaviors, traffic flows, and biological sign…
Sage Deer: A Super-Aligned Driving Generalist Is Your Copilot
Hao Lu, Jiaqi Tang, Jiyao Wang +14
The intelligent driving cockpit, an important part of intelligent driving, needs to match different users' comfort, interaction, and safety needs. This paper aims to build a Super-…
FedGT: Federated Node Classification with Scalable Graph Transformer
Zaixi Zhang, Qingyong Hu, Yang Yu +2
Graphs are widely used to model relational data. As graphs are getting larger and larger in real-world scenarios, there is a trend to store and compute subgraphs in multiple local…