Good Papers

Showing papers from University of Exeter Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Saarland University, UniversitätTianjin University of TechnologyU MacauU ExeterExplainable AI

Interpretable but Fragile? Robustness of Concept Bottlenecks under Geometric-Semantic Perturbations

Hanwei Zhang, Tianma Hu, Gaojie Jin, Xu Cheng and 1 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · 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 2026U Science and Technology of ChinU LiverpoolU DundeeU ExeterAdversarial robustness

Manifold-Aligned Adversarial Perturbation for Anti-Customization under Diffusion-based Purification

Ruotian Liu, Zhen Chen, Zhiguo Yang, Xiangyu Yin 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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Universitat Autònoma de BarcelonU Exeter"Computer Vision Center, BaIndian Statistical InstituteU SurreyMechanistic interpretability

Can Circuit Alignment Predict OOD Generalization?

Ayan Banerjee, ABHRA CHAUDHURI, Josep Llados, Umapada Pal and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · 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
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Science and Technology of ChinU DundeeU ExeterBackdoors & data poisoning

When Sanitization Becomes the Trigger: Defense-Triggered Backdoor Attacks

Zhiguo Yang, Ruotian Liu, Peipei Xu, Wenjie Ruan

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

– ReadersNo votes yet
2/20 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: 2 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 1/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U ExeterAdversarial robustness

Do Not Let Spikes Flip: Margin-Resculpted Learning for Robust Spiking Neural Networks

Desong Zhang, Jia Hu, Geyong Min

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · 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
NeurIPS 2026U ExeterCentral SouthEarlham InstituteMolecules & drug discovery

TANGO: RNA Topology and Geometry Co-Design

Tianmeng Hu, Biao Luo, Ke Li

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U LeicesterNanchangZhejiangU ExeterFederated learning

FedAdaVR: Adaptive Variance Reduction for Robust Federated Learning under Limited Client Participation

FedAdaVR combines adaptive optimization with variance reduction using stored updates to eliminate partial participation error in federated learning, and FedAdaVR-Quant cuts memory by up to 87.5%.

S M RUHUL KABIR HOWLADER, Xiao Chen, Yifei Xie, Lu Liu

Sydney Poster Session 1, Tue, Dec 8, 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 4/5
medium 6/10
strict 1/5
80%Must read
?Must readVote to see the score
NeurIPS 2026AaltoKing's College London, UnivQueen Mary, University of LondonXi'an JiaotongKing's College LondonFairness & bias

FairMT: Fairness for Heterogeneous Multi-Task Learning

FairMT introduces a unified fairness framework for heterogeneous multi-task learning with partial labels, using asymmetric constraint aggregation and head-aware optimization to improve fairness without sacrificing utility.

Guanyu Hu, Tangzheng Lian, Na Yan, Dimitrios Kollias and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · 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 4/5
medium 7/10
strict 1/5
89%Must read
?Must readVote to see the score
NeurIPS 2026U CambridgeU OxfordU Colorado at BoulderU BristolPurdueWeather & climate

ThousandWorlds: A benchmark for climate emulation of potentially habitable exoplanets

ThousandWorlds introduces a multi-model exoplanet climate benchmark of ~1,700 GCM simulations, showing Gaussian processes outperform deep learning in low-data multi-simulator regression.

Edward Stevenson, Mei T Mak, Eric Wolf, Denis E Sergeev and 3 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 1 on Hugging Face

– 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
80%Must read
?Must readVote to see the score
NeurIPS 2026China University of GeosciencesKing Abdullah University of ScieEindhoven University of TechnoloU ExeterChina University of GeoscienceVision-language models

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation

LithoBench evaluates large multimodal models on remote-sensing lithology interpretation via expert-annotated multi-level tasks, revealing substantial limitations in geological reasoning.

jun wang, Fengpeng Li, Tianjin Huang, Hang Dong and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · 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 5/10
strict 2/5