activity
20232026
most citedKimi K2: Open Agentic Intelligence

14 citations · 16 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026★ 2 cited

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +333

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.CL2025

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments

Zhiyuan Zeng, Hamish Ivison, Yiping Wang +14

We introduce Reinforcement Learning (RL) with Adaptive Verifiable Environments (RLVE), an approach using verifiable environments that procedurally generate problems and provide alg…

cs.LG2025★ 14 cited

Kimi K2: Open Agentic Intelligence

Kimi Team, Yifan Bai, Yiping Bao +195

We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…

cs.CV2024

Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability

Zhuorui Ye, Farzan Farnia

Saliency maps have been widely used to interpret the decisions of neural network classifiers and discover phenomena from their learned functions. However, standard gradient-based m…

cs.CL2024

Sing it, Narrate it: Quality Musical Lyrics Translation

Zhuorui Ye, Jinhan Li, Rongwu Xu

Translating lyrics for musicals presents unique challenges due to the need to ensure high translation quality while adhering to singability requirements such as length and rhyme. E…

cs.CV2023

Semantic Complete Scene Forecasting from a 4D Dynamic Point Cloud Sequence

Zifan Wang, Zhuorui Ye, Haoran Wu +2

We study a new problem of semantic complete scene forecasting (SCSF) in this work. Given a 4D dynamic point cloud sequence, our goal is to forecast the complete scene corresponding…

cs.CL2023

Autonomous Tree-search Ability of Large Language Models

Zheyu Zhang, Zhuorui Ye, Yikang Shen +1

Large Language Models have excelled in remarkable reasoning capabilities with advanced prompting techniques, but they fall short on tasks that require exploration, strategic foresi…