Good Papers

Showing papers from University of Manitoba Show all papers

45%Niche pick
?Niche pickVote to see the score

Orthogonal Updates for the Win: Towards Accelerated Adaptive Minimax Optimization

Zhiwei Zhai, Xinyu Wang, Wenjing Yan, Lei Ding and 1 more

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

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

HandXFM: Semantic-Structural Distillation for Hand Radiograph Foundation Models

Yuxi Long, Ganlin Feng, Lianghong Chen, Liam J O'Neil and 2 more

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

– ReadersNo votes yet
1/20 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: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

A Topological Encoder Decoder Framework for Temporal Graph Learning

Ronan Buck, Kiarash Shamsi, Tran Gia Bao Ngo, Astrit Tola and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score

Hydra: Towards Transferable Multi-Task Learning on Temporal Graphs

Kiarash Shamsi, Farimah Poursafaei, Tran Gia Bao Ngo, Reihaneh Rabbany and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
89%Must read
?Must readVote to see the score

From Table to Cell: Attention for Better Reasoning with TABALIGN

TABALIGN improves multi-step table reasoning by pairing diffusion planners generating binary cell masks with attention verifiers, raising accuracy 15.76 points and accelerating execution 44.64%.

Tung Sum Thomas Kwok, Zeyong Zhang, Xinyu Wang, Chunhe Wang and 5 more

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

– ReadersNo votes yet
16/20 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: 16 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 3/5