Papers
Graph Inverse Style Transfer for Counterfactual Explainability
Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton et al.
Self-Consistency Preference Optimization
Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang et al.
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.
DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser et al.
Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI
Julien Pourcel, Cédric Colas, Pierre-Yves Oudeyer
The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
Thomas Pouplin, Kasia Kobalczyk, Hao Sun et al.
Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings
Angéline Pouget, Mohammad Yaghini, Stephan Rabanser et al.
Vintix: Action Model via In-Context Reinforcement Learning
Andrei Polubarov, Lyubaykin Nikita, Alexander Derevyagin et al.
Avoiding Catastrophe in Online Learning by Asking for Help
Benjamin Plaut, Hanlin Zhu, Stuart Russell
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur et al.
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
Constrained Belief Updates Explain Geometric Structures in Transformer Representations
Mateusz Piotrowski, Paul M. Riechers, Daniel Filan et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
Emile Pierret, Bruno Galerne
Privacy Amplification Through Synthetic Data: Insights from Linear Regression
Clément Pierquin, Aurélien Bellet, Marc Tommasi et al.
Revisiting Unbiased Implicit Variational Inference
Tobias Pielok, Bernd Bischl, David Rügamer
Conditioning Diffusions Using Malliavin Calculus
Jakiw Pidstrigach, Elizabeth Louise Baker, Carles Domingo-Enrich et al.
Boosting Masked ECG-Text Auto-Encoders as Discriminative Learners
Manh Pham Hung, Aaqib Saeed, Dong Ma
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
Ngoc-Quan Pham, Tuan Truong, Quyen Tran et al.
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le-Tuyet-Nhi Pham, Dario Shariatian, Antonio Ocello et al.
Gandalf the Red: Adaptive Security for LLMs
Niklas Pfister, Václav Volhejn, Manuel Knott et al.
Wasserstein Policy Optimization
David Pfau, Ian Davies, Diana L Borsa et al.