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From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.CV2026

Beyond Correctness: Benchmarking and Aligning Response Behaviors in Hybrid-Thinking MLLMs

Xinming Wang, Weinong Wang, Hongming Yang +13

Hybrid-thinking multimodal large language models (MLLMs) allow a single model to alternate between deliberative thinking and latency-efficient non-thinking inference. Although thes…

cs.CV2026

HyMobileAgent: Data-Environment Co-Scaling for Efficient GUI Agents

Hy Vision Team, Huawen Shen, Zhengyang Tang +20

The paper introduces HyMobileAgent, a vision-native mobile GUI agent that combines large multimodal models with a co-scaling framework for data and environments to enable precise p…

cs.CV2026

Claim-Level Rubric Rewards for Video Caption Reinforcement Learning

Mingqi Gao, Hongyuan Dong, Yifei Chen +6

In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinforcement learning for dense vi…

cs.CV2026

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

Gengluo Li, Xingyu Wan, Shangpin Peng +20

We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, information extraction, text-image tr…

cs.CL2026

PhoneBuddy: Training Open Models for Agentic Phone Use

Zhengyang Tang, Xin Lai, Pengyuan Lyu +23

Phones are becoming an important execution surface for general-purpose agents, but training open models for reliable phone use remains difficult because the environment that matter…

cs.CL2026

PhoneHarness: Harnessing Phone-Use Agents through Mixed GUI, CLI, and Tool Actions

Chenxin Li, Zhengyao Fang, Zhengyang Tang +18

Phone agents are increasingly expected to complete real mobile workflows rather than merely predict the next screen action. However, much of the current mobile-agent literature sti…