most citedEfficient Reinforcement Learning with Semantic and Token Entropy for LLM Reasoning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2026★ 1 cited

Efficient Reinforcement Learning with Semantic and Token Entropy for LLM Reasoning

Hongye Cao, Zhixin Bai, Ziyue Peng +5

Reinforcement learning with verifiable rewards (RLVR) has demonstrated superior performance in enhancing the reasoning capability of large language models (LLMs). However, this acc…

cs.CR2025

: A Pluggable and Dynamic DoS-Defense Framework Against Resource Consumption Attacks Targeting Large Language Models

Yuanhe Zhang, Xinyue Wang, Haoran Gao +4

Large Language Models (LLMs), due to substantial computational requirements, are vulnerable to resource consumption attacks, which can severely degrade server performance or even c…