most citedBabyVision: Visual Reasoning Beyond Language

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

collaborators

6 papers

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.CV2026

EgoCS-400K: An Egocentric Gameplay Dataset for World Models

Rongjin Guo, Dong Liang, Yuhao Liu +4

The shift from video generation to interactive world modeling places new demands on data: beyond captioned videos, world models require temporally aligned video-action-language tra…

cs.CV2026

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs

Liang Yao, Shengxiang Xu, Fan Liu +7

Earth Observation (EO) systems are essentially designed to support domain experts who often express their requirements through vague natural language rather than precise, machine-f…

cs.CV2026

HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

Tencent Robotics X, HY Vision Team, : +20

We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Vision-Language Models (VLMs) an…

cs.CL2025

A Survey of Reinforcement Learning for Large Reasoning Models

Kaiyan Zhang, Yuxin Zuo, Bingxiang He +36

In this paper, we survey recent advances in Reinforcement Learning (RL) for reasoning with Large Language Models (LLMs). RL has achieved remarkable success in advancing the frontie…

cs.LG2025

xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations

Kaiyuan Chen, Yixin Ren, Yang Liu +30

We introduce xbench, a dynamic, profession-aligned evaluation suite designed to bridge the gap between AI agent capabilities and real-world productivity. While existing benchmarks…