works on
large language models 1LoRA adapters 1online policy optimization 1reasoning 1test-time training 1

From the 1 of 6 linked papers with an AI index.

most citedMemory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.AIShow all

2 papers · 1 filter

cs.AI2026

Policy of Thoughts: Scaling Test-Time Training for LLM Reasoning via Online Policy Evolution

Zhengbo Jiao, Hongyu Xian, Qinglong Wang +5

The paper introduces Policy of Thoughts (PoT), a test‑time training framework that continuously updates a lightweight LoRA adapter using online policy optimization to improve large…

cs.AI2026

DeepLook: Deeper Thinking with Lookahead

Tingxin Yang, Zefeng Wang, Mengyue Wang +2

Inference-time scaling has emerged as a powerful paradigm for improving large language model reasoning, often delivering larger gains on difficult reasoning tasks than parameter sc…