works on

From the 1 of 40 linked papers with an AI index.

activity
20242026
collaborators

40 papers

cs.AI2026

SpatialCLI: Learning to Reason With Spatial Tools, Then Without Them

Yang Zhou, Zixuan Huang, Sunzhu Li +10

The paper presents SpatialCLI, a framework that teaches vision-language models to use specialist visual tools for spatial reasoning and then internalize those capabilities, dramati…

cs.LG2026

Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning

Zetian Hu, Shunyu Liu, Junjie Zhang +4

Recent breakthroughs of Reinforcement Learning (RL) have highlighted its potential for complex agentic Large Language Model (LLM) tasks. However, existing efforts largely focus on…

cs.AI2026

OpenClaw-Skill: Collective Skill Tree Search for Agentic Large Language Models

Tianyi Lin, Chuanyu Sun, Jingyi Zhang +6

Equipping Large Language Model (LLM) agents with effective skills is crucial for solving complex tasks in real-world systems like OpenClaw. In this work, we aim to develop a framew…

cs.LG2026

R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?

Jingyi Zhang, Tianyi Lin, Huanjin Yao +3

In this work, we aim to develop effective data synthesis techniques that autonomously synthesize multimodal training data for enhancing MLLMs in solving complex real-world tasks. T…

cs.LG2026

BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning

Yunpeng Qing, Yixiao Chi, Shuo Chen +5

Recent advances in offline Reinforcement Learning (RL) have proven that effective policy learning can benefit from imposing conservative constraints on pre-collected datasets. Howe…

cs.LG2026

STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning

Junjie Zhang, Guozheng Ma, Shunyu Liu +5

Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs). However, existing step-level…