most citedBabyVision: Visual Reasoning Beyond Language

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

collaborators

8 papers

cs.CV2026

SafeCap: Improving LVLM Safety with Image Captioning Reinforcement Learning

Caoyuan Ma, Wenpu Liu, Weichu Xie +12

Large vision-language models (LVLMs) remain vulnerable to jailbreak attacks that exploit visual inputs to bypass safety alignment inherited from their language backbones. We propos…

cs.CV20261 cited

BabyVision: Visual Reasoning Beyond Language

Liang Chen, Weichu Xie, Yiyan Liang +27

While humans develop core visual skills long before acquiring language, contemporary Multimodal LLMs (MLLMs) still rely heavily on linguistic priors to compensate for their fragile…

cs.LG2026

Leveraging Error Diversity in Group Rollouts for Reinforcement Learning

Wenpu Liu, Yuqi Xu, Weichu Xie +8

Reinforcement Learning from Verifiable Rewards (RLVR) typically samples multiple responses per prompt and assigns binary rewards based on individual correctness, yet the collective…

cs.LG2026

Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning

Ziyue Wang, Aomufei Yuan, Yongfu Zhu +10

Reinforcement Learning from Verifiable Rewards (RLVR) has become the dominant approach for improving mathematical reasoning in large language models, yet current methods reduce eac…

cs.AI2026

SaaS-Bench: Can Computer-Use Agents Leverage Real-World SaaS to Solve Professional Workflows?

Kean Shi, Zihang Li, Tianyi Ma +13

Computer-Using Agents (CUAs) are rapidly extending large language models (LLMs) beyond text-based reasoning toward action execution in more complex environments, such as web browse…

cs.SE2026

RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades

Xinbo Xu, Ruihan Yang, Haiyang Shen +13

Coding agents are increasingly deployed in real software development, where a single version iteration requires months of coordinated work across many files. However, most existing…