most citedAI Scientists for Building Virtual-Cell Models

3 citations · 4 across the 6 of their papers we have counts for

collaborators

8 papers

cs.RO2026

SLIM-0.5B: Learning Action-Grounded Predictive Latents for Robot Manipulation

Jingkai Wang, Zihan Tang, Gu Zhang +7

Vision-language-action policies rely on large multimodal backbones to jointly perform perception, language conditioning, and action generation at every control step. Much of this c…

cs.CV2026

Kwai Keye-VL-2.0 Technical Report

Kwai Keye Team, Bin Wen, Changyi Liu +50

We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding and agentic intelligence. To…

cs.CL2025

Eigen-Agent: Adaptive Multi-Agent Scientific Reasoning with Monitor-Based RAG

Xiangru Tang, Wanghan Xu, Yujie Wang +13

Large language models (LLMs) have recently shown strong progress on scientific reasoning, yet two major bottlenecks remain. First, explicit retrieval fragments reasoning, imposing…

cs.IR2025

OneRec-V2 Technical Report

Guorui Zhou, Hengrui Hu, Hongtao Cheng +72

Recent breakthroughs in generative AI have transformed recommender systems through end-to-end generation. OneRec reformulates recommendation as an autoregressive generation task, a…

cs.LG2025★ 3 cited

AI Scientists for Building Virtual-Cell Models

Xiangru Tang, Zhuoyun Yu, Jiapeng Chen +12

Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hypotheses. Whether they can go further…

cs.IR2025

OneRec Technical Report

Guorui Zhou, Jiaxin Deng, Jinghao Zhang +62

Recommender systems have been widely used in various large-scale user-oriented platforms for many years. However, compared to the rapid developments in the AI community, recommenda…

cs.AI2025★ 1 cited

Advancing AI Research Assistants with Expert-Involved Learning

Tianyu Liu, Simeng Han, Hanchen Wang +27

Large language models (LLMs) and large multimodal models (LMMs) promise to accelerate biomedical discovery, yet their reliability remains unclear. We introduce ARIEL (AI Research A…

cs.CL2025

MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworks

Yanjun Shao, Xiangru Tang, Jiwoong Sohn +10

Complex medical reasoning requires integrating heterogeneous clinical evidence across multiple inference steps. Large language models (LLMs) now approach this through two routes: i…