adaptive training 1curriculum learning 1kalman filter 1large language models 1prompt selection 1reinforcement learning 1
From the 1 of 6 linked papers with an AI index.
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cs.LG2026
Kalman Meets Curriculum: Efficient Dynamic Prompt Selection for Adaptive RL Finetuning
Haodong Zhu, Yangyang Ren, Yanjing Li +4
The paper introduces Kalman-Guided Prompt Selection (KGPS), a method that treats prompt difficulty as a dynamic state estimated with a Kalman filter to adaptively choose prompts du…
cs.LG2026
Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization
Haodong Zhu, Yangyang Ren, Yanjing Li +6
Group Relative Policy Optimization (GRPO) effectively scales LLM reasoning but incurs prohibitive computational costs due to its extensive group-based sampling requirement. While r…
cs.LG2025
Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method
Qingcheng Zhu, Yangyang Ren, Linlin Yang +9
Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can significantly reduce storage and…