Jayneel Parekh

22 papers A* 5B 1Misc 1Journal 11Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Analyzing Fine-tuning Representation Shift for Multimodal LLMs Steering alignment.
CoRR
Pegah Khayatan, Mustafa Shukor, Jayneel Parekh, Matthieu Cord
2025 J jnl
Learning to Steer: Input-dependent Steering for Multimodal LLMs.
CoRR
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Arnaud Dapogny, Alasdair Newson, Matthieu Cord
2025 A* conf
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution.
ICML
Gabriel Kasmi, Amandine Brunetto, Thomas Fel, Jayneel Parekh
2025 A* conf
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models.
ICLR
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
2024 A* conf
A Concept-Based Explainability Framework for Large Multimodal Models.
NeurIPS
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord
2024 J jnl
A Concept-Based Explainability Framework for Large Multimodal Models.
CoRR
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord
2024 J jnl
One Wave to Explain Them All: A Unifying Perspective on Post-hoc Explainability.
CoRR
Gabriel Kasmi, Amandine Brunetto, Thomas Fel, Jayneel Parekh
2024 J jnl
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models.
CoRR
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
2024 J jnl
Tackling Interpretability in Audio Classification Networks With Non-negative Matrix Factorization.
IEEE ACM Trans. Audio Speech Lang. Process.
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
2023 J jnl
Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization.
CoRR
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Gaël Richard, Florence d'Alché-Buc
2023 — —
Un cadre flexible pour l'apprentissage automatique interprétable: application à la classification d'images et d'audio. (A Flexible Framework for Interpretable Machine Learning: application to image and audio classification).
Jayneel Parekh
2022 A* conf
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF.
NeurIPS
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
2022 J jnl
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF.
CoRR
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard
2021 A* conf
A Framework to Learn with Interpretation.
NeurIPS
Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
2020 J jnl
A Framework to Learn with Interpretation.
CoRR
Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
2020 J jnl
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach.
CoRR
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020 — conf
Identifying the "right" level of explanation in a given situation.
NeHuAI@ECAI
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020 Misc conf
Speech-To-Singing Conversion in an Encoder-Decoder Framework.
ICASSP
Jayneel Parekh, Preeti Rao, Yi-Hsuan Yang
2020 J jnl
Speech-to-Singing Conversion in an Encoder-Decoder Framework.
CoRR
Jayneel Parekh, Preeti Rao, Yi-Hsuan Yang
2018 B conf
Deep Pairwise Classification and Ranking for Predicting Media Interestingness.
ICMR
Jayneel Parekh, Harshvardhan Tibrewal, Sanjeel Parekh
2017 — conf
The IITB Predicting Media Interestingness System for MediaEval 2017.
MediaEval
Jayneel Parekh, Harshvardhan Tibrewal, Sanjeel Parekh
2016 — conf
The MLPBOON Predicting Media Interestingness System for MediaEval 2016.
MediaEval
Jayneel Parekh, Sanjeel Parekh