Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
ArXivCSExplorer
☆☆Bookmarks🏆RSSHow to UseFAQ
Home/Authors/Alan Yuille

Alan Yuille

4 indexed papers

Recent (6 mo)
4
With code
0
Influential cites
0
Benchmarked
0

Publications per year

4
26

Top categories

Vision×3AI×3Graphics×2ML×1Comp. Eng.×1Info Retrieval×1

Frequent co-authors

Prakhar Kaushik2×
Soumava Paul2×
Srinjay Sarkar1×
Yi Cao1×
Liaoyaqi Wang1×
Jieneng Chen1×

Research Timeline

2026
RATS! Patches Talk Through Registers: Emergent Parts in Register Attention Transformers

This paper proposes a self-supervised visual model called RATS that discovers compositional structure in images.

ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery

This paper introduces ARIA, a causal-aware framework for materials discovery that mitigates contextual tunneling in Large Language Models.

FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets

This paper presents an efficient method for reconstructing and editing animal fur from multi-view images.

Honeycomb-Surfels: Compact Hexagonal Primitives for Efficient Scene Rendering and Reconstruction

This paper introduces Hexels, a novel planar hexagonal surface element for efficient 3D scene and 2D image representation.

Highlighted terms show continued research focus across papers

Papers

cs.CVcs.AIcs.GREmpiricalRecentOct 27, 2026

Honeycomb-Surfels: Compact Hexagonal Primitives for Efficient Scene Rendering and Reconstruction

Prakhar Kaushik, Soumava Paul, Alan Yuille

This paper introduces Hexels, a novel planar hexagonal surface element for efficient 3D scene and 2D image representation.

View →
cs.CVcs.AIcs.GREmpirical
Recent
Sep 28, 2026

FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets

Srinjay Sarkar, Prakhar Kaushik, Soumava Paul, Alan Yuille

This paper presents an efficient method for reconstructing and editing animal fur from multi-view images.

View →
cs.AIcs.CEcs.IREmpiricalRecentJun 21, 2026

ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery

Yi Cao, Liaoyaqi Wang, Jieneng Chen, Benjamin Van Durme +2 more

This paper introduces ARIA, a causal-aware framework for materials discovery that mitigates contextual tunneling in Large Language Models.

View →
cs.CVEmpiricalRecentJun 12, 2026

RATS! Patches Talk Through Registers: Emergent Parts in Register Attention Transformers

Timing Yang, Predrag Neskovic, Jansen Seheult, Wenchao Han +3 more

This paper proposes a self-supervised visual model called RATS that discovers compositional structure in images.

View →