7 citations · 14 across the 8 of their papers we have counts for
8 papers
CogArena: A Multimethod Evaluation of Cognitive Ability Structure in Large Language Models
Dengzhe Hou, Lingyu Jiang, Fangzhou Lin +1
LLM cognitive scores are increasingly summarized as per-ability profiles whose dimensions should converge across tasks, respond selectively to matched interventions, and generalize…
Same Brain, Different Prediction: How Preprocessing Choices Undermine EEG Decoding Reliability
Dengzhe Hou, Zihao Wu, Lingyu Jiang +3
Electroencephalography (EEG) is a cornerstone of brain-computer interfaces and clinical neuroscience, yet deep learning models are typically trained and evaluated under a single, u…
WMF-AM: Probing LLM Working Memory via Depth-Parameterized Cumulative State Tracking
Dengzhe Hou, Lingyu Jiang, Deng Li +3
Existing large language models (LLMs) evaluations use fixed-difficulty benchmarks that cannot adapt as models improve, and rarely isolate specific cognitive processes. We introduce…
KANMixer: a minimal KAN-centered mixer for long-term time series forecasting
Lingyu Jiang, Dengzhe Hou, Yuping Wang +9
Long-term time series forecasting (LTSF) underpins critical applications from energy management to weather prediction, yet achieving reliable multi-step-ahead accuracy remains chal…
A Language Anchor-Guided Method for Robust Noisy Domain Generalization
Zilin Dai, Lehong Wang, Fangzhou Lin +5
Real-world machine learning applications often struggle with two major challenges: distribution shift and label noise. Models tend to overfit by focusing on redundant and uninforma…
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance
Fangzhou Lin, Haotian Liu, Haoying Zhou +6
3D point clouds enhanced the robot's ability to perceive the geometrical information of the environments, making it possible for many downstream tasks such as grasp pose detection…
Understanding Hyperbolic Metric Learning through Hard Negative Sampling
Yun Yue, Fangzhou Lin, Guanyi Mou +1
In recent years, there has been a growing trend of incorporating hyperbolic geometry methods into computer vision. While these methods have achieved state-of-the-art performance on…
Hyperbolic Contrastive Learning
Yun Yue, Fangzhou Lin, Kazunori D Yamada +1
Learning good image representations that are beneficial to downstream tasks is a challenging task in computer vision. As such, a wide variety of self-supervised learning approaches…