Sayna Ebrahimi

According to our database1, Sayna Ebrahimi authored at least 35 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
ATLAS: Adaptive Transfer Scaling Laws for Multilingual Pretraining, Finetuning, and Decoding the Curse of Multilinguality.
CoRR, October, 2025

Reverse Thinking Makes LLMs Stronger Reasoners.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level Alignment.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction.
Trans. Mach. Learn. Res., 2024

Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence.
CoRR, 2024

CROME: Cross-Modal Adapters for Efficient Multimodal LLM.
CoRR, 2024

Mitigating Object Hallucination via Data Augmented Contrastive Tuning.
CoRR, 2024

TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Test-Time Adaptation for Visual Document Understanding.
Trans. Mach. Learn. Res., 2023

PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series.
CoRR, 2023

LANISTR: Multimodal Learning from Structured and Unstructured Data.
CoRR, 2023

Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Beyond Invariance: Test-Time Label-Shift Adaptation for Distributions with "Spurious" Correlations.
CoRR, 2022

Self-Supervised Pretraining Improves Self-Supervised Pretraining.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Contrastive Test-Time Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
On-target Adaptation.
CoRR, 2021

Region-level Active Learning for Cluttered Scenes.
CoRR, 2021

Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting.
Proceedings of the 9th International Conference on Learning Representations, 2021

Predicting with Confidence on Unseen Distributions.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Mechanical Behavior of Materials at Multiscale Peridynamic Theory and Learning-based Approaches.
PhD thesis, 2020

Compositional GAN: Learning Image-Conditional Binary Composition.
Int. J. Comput. Vis., 2020

Minimax Active Learning.
CoRR, 2020

Uncertainty-guided Continual Learning with Bayesian Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Adversarial Continual Learning.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Compositional GAN (Extended Abstract): Learning Image-Conditional Binary Composition.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Variational Adversarial Active Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Generalized Zero-Shot Learning via Aligned Variational Autoencoders.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

WiCV 2019: The Sixth Women In Computer Vision Workshop.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
Compositional GAN: Learning Conditional Image Composition.
CoRR, 2018

2017
Gradient-free Policy Architecture Search and Adaptation.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017


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