activity
20242026
most citedGLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

4 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2026

AtlasVLA: Persistent World-Ego State Modeling for Vision-Language-Action Models

Guiyu Zhao, Longteng Guo, Yanghong Mei +7

While Vision-Language-Action (VLA) models have advanced embodied AI, their fundamentally reactive paradigm severely limits performance in partially observable and long-horizon task…

cs.AI2026

When Robots Do the Chores: A Benchmark and Agent for Long-Horizon Household Task Execution

Zilin Zhu, Longteng Guo, Yanghong Mei +5

Long-horizon household tasks demand robust high-level planning and sustained reasoning capabilities, which are largely overlooked by existing embodied AI benchmarks that emphasize…

cs.LG2026

Compander-Aligned Query Geometry for Quantized Zeroth-Order Optimization

Yao Shu, Zilin Zhu

Low-bit forward evaluation is an attractive route to memory-efficient zeroth-order (ZO) adaptation: the optimizer needs only scalar losses, and the model can be queried near deploy…

cs.LG2025

APRIL: Active Partial Rollouts in Reinforcement Learning to Tame Long-tail Generation

Yuzhen Zhou, Jiajun Li, Yusheng Su +15

Reinforcement learning (RL) has become a cornerstone in advancing large-scale pre-trained language models (LLMs). Successive generations, including GPT-o series, DeepSeek-R1, Kimi-…

cs.CL2025★ 4 cited

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

5 Team, Aohan Zeng, Xin Lv +167

We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…

cs.AI2024★ 1 cited

OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Jian Hu, Xibin Wu, Wei Shen +12

Large Language Models (LLMs) fine-tuned via Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning with Verifiable Rewards (RLVR) significantly improve the al…