2 citations · 3 across the 16 of their papers we have counts for
4 papers · 1 filter
CVPO: Enhancing LLM Reinforcement Learning Reasoning via Value-Variance Adaptation and Dynamic Curriculum Learning
Ziqi Jia, Yalu Ouyang, Bo Pang +5
Reinforcement learning (RL) has emerged as an effective method for enhancing the reasoning capabilities of large language models (LLMs). However, existing methods suffer from insuf…
Harness Engineering for LLM-Driven GPU Kernel Generation
Yue Shui, Chenyu Ma, Hangfei Xu +2
Large language models (LLMs) can assist GPU kernel generation, but their practical effectiveness depends on whether generated code can be reliably constrained, validated, profiled,…
RADAR: Revealing Asymmetric Development of Abilities in MLLM Pre-training
Yunshuang Nie, Bingqian Lin, Minzhe Niu +7
Pre-trained Multi-modal Large Language Models (MLLMs) provide a knowledge-rich foundation for post-training by leveraging their inherent perception and reasoning capabilities to so…
Dependently-Typed AARA: A Non-Affine Approach for Resource Analysis of Higher-Order Programs
Han Xu, Di Wang
Static resource analysis determines the resource consumption (e.g., time complexity) of a program without executing it. Among the numerous existing approaches for resource analysis…