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Showing papers from Lambda, Inc Show all papers

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NeurIPS 2026U California Santa BarbaraIndian Institute of Technology, U California, San DiegoLambda, IncLambdaControllable generation

OverLay++: Dense-Overlap Layout-to-Image Generation Dataset

Shivansh Aggarwal, Shresth Grover, Divyansh Srivastava, Haiyang Xu and 6 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Texas A&MTexas A&MLambda, IncLambdaRepresentation & contrastive learning

Spin-Weighted Spherical Harmonics Enable Complete and Scalable E(3)-Equivariant Networks

Chenxing Liang, Yuchao Lin, Andrii Kryvenko, Wendi Yu and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026EPFLUniversitat Politècnica de CatalEPFL: Ecole Polytechnique FederaTokyo University, Tokyo InstitutEPFL - EPF LausanneUnified multimodal models

Bridging 1D, 2D, and 3D with Any-to-Any Multimodal Modeling

Jason Toskov, Oriol Barbany, Rishubh Singh, Jinya Sakurai and 9 more

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

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NeurIPS 2026Stevens Institute of TechnologyLambdaColumbiaU Texas Health Science Center atStevens Institute of Technology;LLM pretraining & scaling laws

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation

RISE sketches LLM output-layer influence hotspots into compressed dual-channel sketches, reducing storage up to 112x versus gradient methods while scaling to 32B parameters for attribution and data valuation.

yide ran, Jianwen Xie, Minghui Wang, W. Jim Zheng and 3 more

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

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16/20 AI panelreviewers recommend it

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 2/5