Good Papers

Showing papers from KAUST Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026KAUST / CMUKAUSTKing Abdullah University of ScieVision backbones

OrbitLoRA: Learning Rotation-Aware Low-Data Adaptation of Vision Foundation Models

Yunlu Chen, Dominik Engel, Peter Wonka, Ivan Viola

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026ZhejiangThe State Key Laboratory of BlocIndependentKAUSTKing Abdullah University of SciePrivacy

Ask in the Crowd: Differentially Private LLM Inference via Dummy-Augmented Shuffling

Zhihao Liu, Zixiong Guo, Shuo Shao, Yu He and 4 more

Sydney Poster Session 4, Wed, Dec 9, 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
NeurIPS 2026KAUSTKing Abdullah University of ScieMulti-agent LLM systems

The Reflexivity Threshold: A Phase Transition for Multi-Agent Performative Prediction

Ahmed Mahrous, Roberto Di Pietro

Sydney Poster Session 6, Thu, Dec 10, 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
NeurIPS 2026MBZUAIGeorgia Institute of TechnologyKAUSTU Electronic Science and TechnolLLM evaluation & benchmarks

Hearing is Believing? Evaluating and Analyzing Audio Language Model Sycophancy with SYAUDIO

Junchi Yao, Lokranjan Lakshmikanthan, Annie Zhao, Danielle Zhao and 4 more

Sydney Poster Session 4, Wed, Dec 9, 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
NeurIPS 2026KAUSTOptimization

Rennala-NSGD: Asynchronous Stochastic Optimization Beyond Euclidean Geometry

Igor Sokolov, Alexander Tyurin, Peter Richtarik

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
NeurIPS 2026U Massachusetts BostonState University of New York at SPY Lab -- ETH ZurichBeijing Institute of TechnologyKAUSTDeep RL

Differentially Private Sparse Reward Estimation with Preference Feedback

Meng Ding, Mingxi Lei, Jie Zhang, Jinyan Liu and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · 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
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026UlmGoogle ZurichKAUSTTechnische Universität WienSegmentation

S2D: Sparse-To-Dense Keymask Distillation for Unsupervised Video Instance Segmentation

S2D uses keymask distillation with temporal drop loss to propagate sparse high-quality pseudo-masks across real videos, outperforming synthetic-data methods in unsupervised video instance segmentation.

Leon Sick, Lukas Hoyer, Dominik Engel, Pedro Hermosilla and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face · Code ★ 2

– 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 4/5
medium 5/10
strict 0/5
89%Must read
?Must readVote to see the score
NeurIPS 2026KAUSTKing Abdullah University of ScieInstitute for Computer Science, U BristolCalifornia Academy of SciencesImage recognition

ReefNet: A Large-Scale Dataset and Benchmark for Fine-Grained Coral Reef Recognition

ReefNet provides ~925K genus-level coral annotations and benchmarks showing vision models degrade under zero-shot and cross-source shifts despite adaptation gains.

Abdulwahab Felemban, Yahia Battach, Faizan F Khan, Yuqian Fu and 12 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · 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 5/5
medium 8/10
strict 3/5
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026KAUSTKing Abdullah University of ScieEPFLEfficient & distributed training

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging

LOSCAR-SGD combines local SGD, sparse communication, and overlap with a delay-corrected merge for heterogeneous workers, yielding convergence guarantees and faster training.

Peter Richtarik, Yassine Maziane, Ammar Mahran, Artavazd Maranjyan

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

– ReadersNo votes yet
11/20 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: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
86%Must read
?Must readVote to see the score
NeurIPS 2026EPFLKAUSTFederated learning

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity

Rescaled ASGD corrects asynchronous SGD's bias toward fast workers via computation-time-proportional step sizes, matching optimal time complexity with only lower-order heterogeneity penalties.

Ammar Mahran, Artavazd Maranjyan, Peter Richtarik

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

– ReadersNo votes yet
14/20 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: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5