activity
20232026
most citedMultiscale Positive-Unlabeled Detection of AI-Generated Texts

13 citations · 15 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Seed2Scale: A Self-Evolving Data Engine with Parallel Worlds Expansion for Scalable Robot Learning

Cong Tai, Zhaoyu Zheng, Haixu Long +14

Existing data generation methods for robot learning suffer from limited exploration, embodiment gaps, low signal-to-noise ratios, and domain shifts, leading to performance degradat…

cs.RO2025

RealMirror: A Comprehensive, Open-Source Vision-Language-Action Platform for Embodied AI

Cong Tai, Zhaoyu Zheng, Haixu Long +13

The emerging field of Vision-Language-Action (VLA) for humanoid robots faces several fundamental challenges, including the high cost of data acquisition, the lack of a standardized…

cs.LG2025

UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery

Ruifeng Li, Mingqian Li, Wei Liu +5

Drug discovery is crucial for identifying candidate drugs for various diseases.However, its low success rate often results in a scarcity of annotations, posing a few-shot learning…

cs.LG2024

Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery

Ruifeng Li, Wei Liu, Xiangxin Zhou +4

In the drug discovery process, the low success rate of drug candidate screening often leads to insufficient labeled data, causing the few-shot learning problem in molecular propert…

cs.LG2024

Dual-Label Learning With Irregularly Present Labels

Mingqian Li, Qiao Han, Ruifeng Li +2

In multi-task learning, labels are often missing irregularly across samples, which can be fully labeled, partially labeled or unlabeled. The irregular label presence often appears…

cs.LG2024★ 2 cited

GNN-SKAN: Harnessing the Power of SwallowKAN to Advance Molecular Representation Learning with GNNs

Ruifeng Li, Mingqian Li, Wei Liu +1

Effective molecular representation learning is crucial for advancing molecular property prediction and drug design. Mainstream molecular representation learning approaches are base…

q-bio.QM2024

Physical formula enhanced multi-task learning for pharmacokinetics prediction

Ruifeng Li, Dongzhan Zhou, Ancheng Shen +9

Artificial intelligence (AI) technology has demonstrated remarkable potential in drug dis-covery, where pharmacokinetics plays a crucial role in determining the dosage, safety, and…

cs.CL2023★ 13 cited

Multiscale Positive-Unlabeled Detection of AI-Generated Texts

Yuchuan Tian, Hanting Chen, Xutao Wang +5

Recent releases of Large Language Models (LLMs), e.g. ChatGPT, are astonishing at generating human-like texts, but they may impact the authenticity of texts. Previous works propose…