Good Papers

Showing papers from MILA Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026ConcordiaMILAU TübingenEfficient attention & state-space models

The Kernel Reality Check: Benchmarking and Distilling Efficient Attention at Scale

Firat Oncel, Cem Subakan, Mirco Ravanelli, Çağatay Yıldız

Sydney Poster Session 6, Thu, Dec 10, 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
80%Must read
?Must readVote to see the score
NeurIPS 2026ConcordiaMila - Quebec Artificial IntelliMila - Québec, ServiceNowMilaMILARecommender systems

Controllable and Content Based Recommendations

CCBR builds recommendations from textual user profiles via content-derived text bottlenecks, enabling controllable multimodal steering with competitive accuracy across image, audio, and video datasets.

Firat Oncel, Jihoon Jeong, Emiliano Penaloza, Mirco Ravanelli and 2 more

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

– ReadersNo votes yet
12/20 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: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5