3 citations · 7 across the 12 of their papers we have counts for
13 papers
SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis
Songhan Wang, Haoang Chi, He Li +6
Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics. As the fundamental paradigm for reconstructing cell developmental paths, trajectory inf…
HiFiVe: High-Fidelity Vehicle Generation Leveraging Auto-Regressive 2D Generative Priors
Hongli Xiao, Youjian Zhang, Qi Zheng +5
Existing 3D vehicle generation methods often suffer from low geometric fidelity and blurry textures, hindering their downstream applications. While recent works adopt multi-view di…
3DCarGen: Scalable 3D Car Generation via 3D-consistent Multi-view Synthesis
Hongli Xiao, Youjian Zhang, Yaohui Jin +3
High-quality 3D vehicle assets are essential for autonomous driving simulation. Although multi-view diffusion-based paradigms enable controllable single-image reconstruction, they…
MM-TRELLIS: Point-Cloud Guided Multi-Modal 3D Vehicle Generation in Autonomous Driving
Hongli Xiao, Youjian Zhang, Yucai Bai +5
Recovering realistic 3D vehicle models from autonomous driving scenes is crucial for synthesizing training data and building simulation environment. However, most existing vehicle…
Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
Xinpeng Lv, Yunxin Mao, Renzhe Xu +11
Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes. Existing SC frameworks t…
When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
Xinpeng Lv, Yunxin Mao, Renzhe Xu +13
Tabular foundation models based on pretrained prior-data fitted networks~(PFNs) have shown strong generalization on diverse tabular tasks, but they are typically designed for \emph…
Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
Haoang Chi, He Li, Wenjing Yang +5
Causal reasoning capability is critical in advancing large language models (LLMs) toward strong artificial intelligence. While versatile LLMs appear to have demonstrated capabiliti…
OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data
Fengxiang Wang, Mingshuo Chen, Xuming He +15
Existing benchmarks for multimodal learning in Earth science offer limited, siloed coverage of Earth's spheres and their cross-sphere interactions, typically restricting evaluation…
Look Within, Why LLMs Hallucinate: A Causal Perspective
He Li, Haoang Chi, Mingyu Liu +1
The emergence of large language models (LLMs) is a milestone in generative artificial intelligence, achieving significant success in text comprehension and generation tasks. Despit…
Tackling Noisy Labels with Network Parameter Additive Decomposition
Jingyi Wang, Xiaobo Xia, Long Lan +5
Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows…
EAFP-Med: An Efficient Adaptive Feature Processing Module Based on Prompts for Medical Image Detection
Xiang Li, Long Lan, Husam Lahza +5
In the face of rapid advances in medical imaging, cross-domain adaptive medical image detection is challenging due to the differences in lesion representations across various medic…
A Novel Human-Based Meta-Heuristic Algorithm: Dragon Boat Optimization
Xiang Li, Long Lan, Husam Lahza +5
(Aim) Dragon Boat Racing, a popular aquatic folklore team sport, is traditionally held during the Dragon Boat Festival. Inspired by this event, we propose a novel human-based meta-…
SODA: Robust Training of Test-Time Data Adaptors
Zige Wang, Yonggang Zhang, Zhen Fang +3
Adapting models deployed to test distributions can mitigate the performance degradation caused by distribution shifts. However, privacy concerns may render model parameters inacces…