3 citations · 3 across the 8 of their papers we have counts for
8 papers
Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
He Zhang, Lingzhu Xiang, Haitao Lin +23
In this report, we present Hy-Embodied-0.5-VLA, abbreviated as HyVLA-0.5, an end-to-end system that spans the full robot learning stack: data collection, model design, continued pr…
From Holo Pockets to Electron Density: GPT-style Drug Design with Density
Jiahao Chen, Letian Gao, Yanhao Zhu +4
Recent advances in generative modeling have enabled significant progress in structure-based drug design (SBDD). Existing methods typically condition molecule generation on empty bi…
SciLT: Long-tailed Image Classification under Scientific Image Domains
Jiahao Chen, Bing Su
Long-tailed recognition has benefited from foundation models and fine-tuning paradigms, yet existing studies and benchmarks are mainly confined to natural image domains, where pre-…
LoFT: Parameter-Efficient Fine-Tuning for Long-tailed Semi-Supervised Learning in Open-World Scenarios
Zhiyuan Huang, Jiahao Chen, Bing Su
Long-tailed semi-supervised learning (LTSSL) presents a formidable challenge where models must overcome the scarcity of tail samples while mitigating the noise from unreliable pseu…
LumosFlow: Motion-Guided Long Video Generation
Jiahao Chen, Hangjie Yuan, Yichen Qian +6
Long video generation has gained increasing attention due to its widespread applications in fields such as entertainment and simulation. Despite advances, synthesizing temporally c…
Rethinking the Bias of Foundation Model under Long-tailed Distribution
Jiahao Chen, Bin Qin, Jiangmeng Li +2
Long-tailed learning has garnered increasing attention due to its practical significance. Among the various approaches, the fine-tuning paradigm has gained considerable interest wi…
Interpretable Enzyme Function Prediction via Residue-Level Detection
Zhao Yang, Bing Su, Jiahao Chen +1
Predicting multiple functions labeled with Enzyme Commission (EC) numbers from the enzyme sequence is of great significance but remains a challenge due to its sparse multi-label cl…
Domain-adaptive and Subgroup-specific Cascaded Temperature Regression for Out-of-distribution Calibration
Jiexin Wang, Jiahao Chen, Bing Su
Although deep neural networks yield high classification accuracy given sufficient training data, their predictions are typically overconfident or under-confident, i.e., the predict…