activity
20192026
most citedCausality-driven Hierarchical Structure Discovery for Reinforcement Learning

13 citations · 37 across the 31 of their papers we have counts for

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Showing 2025Show all

11 papers · 1 filter

cs.LG2025

Efficient Diffusion Planning with Temporal Diffusion

Jiaming Guo, Rui Zhang, Zerun Li +7

Diffusion planning is a promising method for learning high-performance policies from offline data. To avoid the impact of discrepancies between planning and reality on performance,…

cs.DC2025

QiMeng-Kernel: Macro-Thinking Micro-Coding Paradigm for LLM-Based High-Performance GPU Kernel Generation

Xinguo Zhu, Shaohui Peng, Jiaming Guo +10

Developing high-performance GPU kernels is critical for AI and scientific computing, but remains challenging due to its reliance on expert crafting and poor portability. While LLMs…

cs.AI2025

Run, Ruminate, and Regulate: A Dual-process Thinking System for Vision-and-Language Navigation

Yu Zhong, Zihao Zhang, Rui Zhang +9

Vision-and-Language Navigation (VLN) requires an agent to dynamically explore complex 3D environments following human instructions. Recent research underscores the potential of har…

cs.AI2025

QiMeng-NeuComBack: Self-Evolving Translation from IR to Assembly Code

Hainan Fang, Yuanbo Wen, Jun Bi +8

Compilers, while essential, are notoriously complex systems that demand prohibitively expensive human expertise to develop and maintain. The recent advancements in Large Language M…

cs.LG2025

QiMeng-CRUX: Narrowing the Gap Between Natural Language and Verilog via Core Refined Understanding eXpression for Circuit Design

Lei Huang, Rui Zhang, Jiaming Guo +9

Large language models (LLMs) have shown promising capabilities in hardware description language (HDL) generation. However, existing approaches often rely on free-form natural langu…

cs.LG2025

QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation

Yang Zhang, Rui Zhang, Jiaming Guo +10

The remarkable progress of Large Language Models (LLMs) presents promising opportunities for Verilog code generation which is significantly important for automated circuit design.…