3 citations · 3 across the 9 of their papers we have counts for
9 papers
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
Quark Medical Alignment: A Holistic Multi-Dimensional Alignment and Collaborative Optimization Paradigm
Tianxiang Xu, Jiayi Liu, Yixuan Tong +10
While reinforcement learning for large language model alignment has progressed rapidly in recent years, transferring these paradigms to high-stakes medical question answering revea…
Tighnari v2: Mitigating Label Noise and Distribution Shift in Multimodal Plant Distribution Prediction via Mixture of Experts and Weakly Supervised Learning
Haixu Liu, Yufei Wang, Tianxiang Xu +2
Large-scale, cross-species plant distribution prediction plays a crucial role in biodiversity conservation, yet modeling efforts in this area still face significant challenges due…
Weak to Strong: VLM-Based Pseudo-Labeling as a Weakly Supervised Training Strategy in Multimodal Video-based Hidden Emotion Understanding Tasks
Yufei Wang, Haixu Liu, Tianxiang Xu +2
To tackle the automatic recognition of "concealed emotions" in videos, this paper proposes a multimodal weak-supervision framework and achieves state-of-the-art results on the iMiG…
Adaptive Disentangled Representation Learning for Incomplete Multi-View Multi-Label Classification
Quanjiang Li, Zhiming Liu, Tianxiang Xu +2
Multi-view multi-label learning frequently suffers from simultaneous feature absence and incomplete annotations, due to challenges in data acquisition and cost-intensive supervisio…
Adaptive Detector-Verifier Framework for Zero-Shot Polyp Detection in Open-World Settings
Shengkai Xu, Hsiang Lun Kao, Tianxiang Xu +9
Polyp detectors trained on clean datasets often underperform in real-world endoscopy, where illumination changes, motion blur, and occlusions degrade image quality. Existing approa…
Hierarchical Dual-Strategy Unlearning for Biomedical and Healthcare Intelligence Using Imperfect and Privacy-Sensitive Medical Data
Yi Zhang, Chao Zhang, Zijian Li +7
Large language models (LLMs) exhibit exceptional performance but pose substantial privacy risks due to training data memorization, particularly within healthcare contexts involving…
Holographic Transformers for Complex-Valued Signal Processing: Integrating Phase Interference into Self-Attention
Enhao Huang, Zhiyu Zhang, Tianxiang Xu +6
Complex-valued signals encode both amplitude and phase, yet most deep models treat attention as real-valued correlation, overlooking interference effects. We introduce the Holograp…
SCORE: Story Coherence and Retrieval Enhancement for AI Narratives
Qiang Yi, Yangfan He, Jianhui Wang +18
Large Language Models (LLMs) can generate creative and engaging narratives from user-specified input, but maintaining coherence and emotional depth throughout these AI-generated st…