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Showing papers from Beijing Academy of Artificial Intelligence Show all papers

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NeurIPS 2026PekingBeijing Academy of Artificial InTsinghuaEmbodied agents

A Latent World-Action Model with Jointly Aligned Reasoning

Hao Luo, Wanpeng Zhang, Yicheng Feng, Sipeng Zheng and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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57%Worth a look
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NeurIPS 2026PekingBeijing Academy of Artificial InHarbin Institute of TechnologyVideo generation

SAX: Advancing Video Diffusion Models for Sequential Action Execution

Haoyu Wang, Baorui Ma, Donglin Di, Shiliang Zhang

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
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NeurIPS 2026Renmin University of ChinaColumbiaBeijing JiaotongU Science and Technology of ChinBeijing Academy of Artificial InAgent benchmarks & environments

SciResearchBench: Benchmarking AI Agents on Complex Scientific Literature Discovery

Lei Xiong, Kun Luo, Ziyi Xia, Wenbo Zhang and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
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NeurIPS 2026BeihangPekingInstitute of automation, ChineseBeijing Academy of Artificial InKuaishou Inc.Robot manipulation

Learning Active Perception and Manipulation via Spatio-temporal Visual Memory

Enshen Zhou, Mengzhen Liu, Yibo Li, Yanjun Ding and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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medium 0/10
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45%Niche pick
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NeurIPS 2026PekingZhongguancun AcademyHarbin Institute of TechnologyBeijing Academy of Artificial InVideo understanding

HyrCap: Hybrid Rank-Calibration of Action Proposals for Temporal Event Understanding

Rui Chen, Xingyu Chen, Pengxin Xu, Kai Chen and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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88%Must read
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NeurIPS 2026Beijing Academy of Artificial InShanghai JiaotongU Electronic Science and TechnolHainanThe Hong Kong University of Scie3D vision & reconstruction

Focusable Monocular Depth Estimation

FocusDepth uses spatially-aligned multi-scale prompt fusion to boost target-region depth accuracy and sharp boundaries while preserving global geometry, outperforming global baselines on FDE-Bench.

Yuxin Du, Tao Lin, Zile Zhong, Runting Li and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
91%Must read
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NeurIPS 2026Beijing Academy of Artificial InBeijing Anzhen Hospital， CapitalBeihangU Science and Technology of ChinBAAIVision-language models

CardioLens: Revealing the Clinical Reality Gap of MLLMs via Multi-Sequence Cardiac MRI Evaluations

CardioLens evaluates MLLMs on multi-sequence cardiac MRI, revealing poor clinical workflow performance and category-collapse failures despite reasoning prompts and slice selection.

Zixian Su, Hongkai Zhang, Fan Gao, Encheng Su and 11 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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18/20 AI panelreviewers recommend it

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AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 5/5
72%Highly rated
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NeurIPS 2026PekingBeijing Academy of Artificial InKuaishou Inc.Vision-language-action models

METIS: Multi-Source Egocentric Training for Integrated Dexterous Vision-Language-Action Model

METIS is a vision-language-action model pretrained on multi-source egocentric data that achieves the highest success rate across six real-world dexterous manipulation tasks.

Yankai Fu, Ning Chen, Junkai Zhao, Shaozhe Shan and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 2/10
strict 1/5
72%Highly rated
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NeurIPS 2026FudanZhongguancun Institute of ArtifiBeijing Academy of Artificial InRobot manipulation

EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields

EA-WM projects robotic actions into camera-aligned visual fields and fuses them via event-aware attention to preserve spatial geometry and interaction dynamics, achieving state-of-the-art results on WorldArena.

Zhaoyang Yang, Yurun Jin, Lizhe Qi, Cong Huang and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 4/5
medium 4/10
strict 0/5
74%Highly rated
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NeurIPS 2026Shanghai JiaotongBeijing Academy of Artificial InTongjiShanghai JiaoTong UnversityInstitute for Computer Science, Vision-language-action models

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

Evo-Depth is a lightweight 0.9-billion-parameter vision-language-action model using implicit depth encoding from RGB to improve spatial manipulation without extra sensors. It achieves top benchmark performance with minimal GPU memory and highest inference speed among compared methods.

Tao Lin, Yuxin Du, Jiting Liu, Nuobei Zhu and 13 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5