Papers
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
Yuliang Liu, Junjie Lu, Chaofeng Qu et al.
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo et al.
AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V Treviso, Andre Martins
AdaWorld: Learning Adaptable World Models with Latent Actions
Shenyuan Gao, Siyuan Zhou, Yilun Du et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang et al.
Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarević, Ravi Hammond, Tobias Gessler et al.
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hohei Chan, Deheng Ye et al.
ADIOS: Antibody Development via Opponent Shaping
Sebastian Rene Towers, Aleksandra Kalisz, Philippe A. Robert et al.
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron J Havens, Benjamin Kurt Miller, Bing Yan et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Lucie Filippi, Mark Van Der Wilk
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte, David Rügamer, Thomas Nagler
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang et al.
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen et al.
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Wei Liu, Zhongyu Niu, Lang Gao et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
Thomas Paniagua, Chinmay Savadikar, Tianfu Wu
Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George J. Pappas et al.
Adversarial Robust Generalization of Graph Neural Networks
Chang Cao, Han Li, Yulong Wang et al.