Good Papers

Showing papers from University at Buffalo Show all papers

72%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Massachusetts AmherstU Massachusetts at AmherstState University of New York at University at BuffaloLearning theory

Intrinsic Riemannian Cross-covariance for Manifold-valued Random Objects

Intrinsic Riemannian cross-covariance defines manifold-valued covariance via parallel transport to a common tangent space, yielding coordinate-independent second-order descriptors with Euclidean-like properties and verified asymptotic behavior.

Carlos Soto, Cheng Wang, Yujing Huang, Xiaoyu Chen

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
8/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 8 of 20 reviewers recommend it
lenient 4/5
medium 4/10
strict 0/5
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Michigan StateState University of New York at University at BuffaloMICHIGAN STATE UNIVERSITYEmbodied agents

Vision to Geometry: 3D Spatial Memory for Sequential Embodied MLLM Reasoning and Exploration

3DSPMR leverages 3D spatial memory with field-of-view geometric priors to reuse exploration knowledge across sequential embodied tasks, significantly improving reasoning and navigation performance on the SEER-Bench benchmark.

Zhongyi Cai, Yi Du, Chen Wang, Yu Kong

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

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