Publications (32)
Contrastive Self-Supervised Learning for Skeleton Representations
Nico Lingg, Miguel Sarabia, Luca Zappella +1
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
Yinong Oliver Wang, Nivedha Sivakumar, Falaah Arif Khan +6
Designing Data: Proactive Data Collection and Iteration for Machine Learning
Aspen Hopkins, Fred Hohman, Luca Zappella +2
DSO: Direct Steering Optimization for Bias Mitigation
Lucas Monteiro Paes, Nivedha Sivakumar, Yinong Oliver Wang +4
Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models
Natalie Mackraz, Nivedha Sivakumar, Samira Khorshidi +4
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
Borja RodrÃguez-Gálvez, Arno Blaas, Pau RodrÃguez +5
LinEAS: End-to-end Learning of Activation Steering with a Distributional Loss
Pau Rodriguez, Michal Klein, Eleonora Gualdoni +5
Homomorphic Self-Supervised Learning
T. Anderson Keller, Xavier Suau, Luca Zappella
Challenges of Adversarial Image Augmentations
Arno Blaas, Xavier Suau, Jason Ramapuram +2
The Design Space of Tri-Modal Masked Diffusion Models
Louis Bethune, Victor Turrisi, Bruno Kacper Mlodozeniec +21
Fair SA: Sensitivity Analysis for Fairness in Face Recognition
Aparna R. Joshi, Xavier Suau, Nivedha Sivakumar +2
Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare
Arno Blaas, Adam GoliÅski, Andrew Miller +3
DUET: 2D Structured and Approximately Equivariant Representations
Xavier Suau, Federico Danieli, T. Anderson Keller +5
Bias after Prompting: Persistent Discrimination in Large Language Models
Nivedha Sivakumar, Natalie Mackraz, Samira Khorshidi +4
DeepPCR: Parallelizing Sequential Operations in Neural Networks
Federico Danieli, Miguel Sarabia, Xavier Suau +2
Finding Experts in Transformer Models
Xavier Suau, Luca Zappella, Nicholas Apostoloff
Filter Distillation for Network Compression
Xavier Suau, Luca Zappella, Nicholas Apostoloff
Self-conditioning pre-trained language models
Xavier Suau, Luca Zappella, Nicholas Apostoloff
Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution
Falaah Arif Khan, Nivedha Sivakumar, Yinong Oliver Wang +5
On The Effectiveness-Fluency Trade-Off In LLM Conditioning: A Systematic Study
Iuri Macocco, Pau RodrÃguez, Arno Blaas +3
Attention to Mamba: A Recipe for Cross-Architecture Distillation
Abhinav Moudgil, Ningyuan Huang, Eeshan Gunesh Dhekane +3
Fairness Dynamics During Training
Krishna Patel, Nivedha Sivakumar, Barry-John Theobald +2
HyperTransport: Amortized Conditioning of T2I Generative Models
Valentino Maiorca, Eleonora Gualdoni, Xavier Suau +3
Spatial LibriSpeech: An Augmented Dataset for Spatial Audio Learning
Miguel Sarabia, Elena Menyaylenko, Alessandro Toso +7
Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results
Andrea Santilli, Adam Golinski, Michael Kirchhof +5
Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts
Jonathan Crabbé, Pau RodrÃguez, Vaishaal Shankar +2
GenCtrl -- A Formal Controllability Toolkit for Generative Models
Emily Cheng, Carmen Amo Alonso, Federico Danieli +4
Controlling Language and Diffusion Models by Transporting Activations
Pau Rodriguez, Arno Blaas, Michal Klein +4
Uncertainty Quantification for LLM Function-Calling
Zihuiwen Ye, Lukas Aichberger, Michael Kirchhof +5
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
Xavier Suau, Pieter Delobelle, Katherine Metcalf +4
ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models
Federico Danieli, Pau Rodriguez, Miguel Sarabia +2
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil +3