PaLoRA: Paced Low-Rank Adaptation for Continual Learning

PaLoRA derives an optimal rank-aware pacing law for LoRA continual learning that adaptively restricts gradient scaling to prevent forgetting, improving long-horizon benchmark accuracy by 4%.

Yuxuan Li, Fanhu Zeng, Hao Tang

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

Test-Time Learning with an Evolving Library

Weijia Xu, Alessandro Sordoni, Chandan Singh, Zelalem Gero and 3 more

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

Inferring learning rules in deep neural network architectures from animal learning data

Shaunak Bhandarkar, Jonathan Pillow

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

MT-CC: Multi-Group Temperature Scaling for Asymmetric Calibration Behavior in Class-Incremental Learning

Sungjun Yun, Yonghee Choi, Dong-Jun Han

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Prediction-only distillation with optimal mixing in ridge-regularized linear and logistic regression

Hien Dang, Pratik Patil, Alessandro Rinaldo

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

From Generic to Dedicated: A Novel Optimizer for Online Continual Learning

Yongyi Wu, Zheng Wang, Sen Lin

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

TailAdapt: Heavy-Tailed Sparse Variational Adaptation for Long-Tailed Class Incremental Learning

Abhishek Kumar Sinha, Nitant Dube, Soma Biswas

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Data-Efficient Learning for Constraint Satisfaction Problems via Relational Biases and Hard Axiom Clamping

Enqiang Zhu, Ke Wang, Yu Zhang, Shengzhi Wang and 2 more

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

Curvature-Guided Parameter Initialization for Multi-Task Learning

Linxiao Cao, Zhipeng Zhou, Xutao Huang, Min Zhou and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Few-shot Task Learning via Compositional Concept Inference

Hanming Ye, Yiding Song, Yilun Du

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

DUST: Directional Uncertainty-aware and Scale-invariant Transfer Learning

Abhisek Chakraborty

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

Improving Neural Processes in the Low-Data Regime via Context-Subset Training and Self-Distillation

Hyungi Lee, Jangho Kim

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

Constrained Modulatory Reservoirs for Context-Dependent Computation

Sejeung Choi, Minji Jung, Jinyeong Park, Taek D Chung

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

Uncertainty Aware SURE Transfer Learning for Classification Problems

Haoyue Li, Shubo Li, Runze Li

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

How deep is your network? Deep vs. shallow learning of transfer operators

Mohammad Tabish, Benedict Leimkuhler, Stefan Klus

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

DnNP: Denoising Input Uncertainty in Neural Processes

Fatemeh Tohidian, Chengzhi Shi, Soomi Lee, Matthew Elia and 3 more

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

Cross-Architecture Transferability is Width-Confounded:Diagnosis and Subspace Correction

QIN LIU, Chen Zhong, Fengshan Zhao

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Re-evaluating Continual Learning with Few-Shot Adaptation

Few-shot evaluation of continual learning reveals that meta-learning future tasks improves per-shot plasticity and stability across sequences.

Amogh Inamdar, Matthew So, Vici I Milenia, Richard Zemel

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

Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective

Existing plasticity diagnostics fail to predict trainability, but optimization readiness, combining gradient strength and reliability, lower-bounds optimization gain and predicts plasticity more reliably.

Jiuqi Wang, Jayanth Srinivasa, Claire Chen, Shuze D Liu and 2 more

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

Trust Region Continual Learning as an Implicit Meta-Learner

Trust region continual learning merges generative replay with Fisher-metric trust regions to implicitly meta-learn rapid task reconvergence without explicit bilevel optimization, outperforming replay and regularization baselines.

Zekun Wang, Anant Gupta, Christopher MacLellan

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

Learning Subspace-Preserving Sparse Attention Graphs from Heterogeneous Multiview Data

SAGL learns subspace-preserving sparse attention graphs from heterogeneous multiview data via bilinear attention and dynamic sparsity gating, outperforming state-of-the-art unsupervised transfer learning methods.

Jie Chen, Yuanbiao Gou, Chuanbin Liu, Zhu Wang and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty

PRISE uses sequential lookahead to select representative scenarios for two-stage robust optimization, while NeurPRISE learns a GNN-Transformer surrogate via imitation learning that achieves 7-200x speedups and strong zero-shot generalization.

TIANJUE LIN, Jianan Zhou, Jieyi Bi, Yaoxin Wu and 3 more

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

SMOG: Scalable Meta-Learning for Multi-Objective Bayesian Optimization

SMOG proposes a scalable multi-output Gaussian process meta-learning model that learns objective correlations to accelerate multi-objective Bayesian optimization with linear meta-task scaling.

Leonard Papenmeier, Petru Tighineanu

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

Aligning Inductive Bias for Data-Efficient Generalization in State Space Models

Aligning SSM inductive bias via spectral matching via task-dependent initialization improves data-efficient generalization when default spectral priors mismatch tasks.

Qiyu Chen, Guozhang Chen

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

Dynamical Adapter Fusion: Constructing A Global Adapter for Pre-Trained Model-based Class-Incremental Learning

Dynamical Adapter Fusion derives optimal coefficients via PAC-Bayes and Taylor expansion to fuse task-specific adapters into one global adapter, achieving state-of-the-art class-incremental learning results.

RuiQi Liu, Boyu Diao, Zijia An, Runjie Shao and 4 more

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

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization

FoMEMO proposes foundation models for expensive multi-objective optimization that use synthetic pre-training and in-context preference-conditioned posteriors to optimize unknown problems without further training.

Yiming Yao, Fei Liu, Liang Zhao, Xi Lin and 2 more

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

In-Context Black-Box Optimization with Unreliable Feedback

FICBO pretrains a feedback-aware transformer to condition on both optimization history and unreliable auxiliary feedback, estimating source reliability in context to improve black-box query selection.

Nicolas Samuel Blumer, Julien Martinelli, Samuel Kaski

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

Hyperparameter Transfer for Dense Associative Memories

Derives explicit hyperparameter transfer rules for Dense Associative Memories and validates them against large-scale training.

Roi Holtzman, Dmitry Krotov, Boris Hanin

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026