Adel Bibi

42 papers · 2016–2025 · 11 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🌍 Conference Polyglot (11) 🏃 Academic Marathon (9) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (8) 🤝 Dynamic Duo (22) 🏆 Grand Slam 🏆 Keyword Champion 👑 Triple Crown 👥 Mega-Team (24) ❓ The Questioner (4) 🗃️ Keyword Collector (125) ⚡ Prolific Year (6) 🚀 Conference Pioneer 📈 Trend Setter 💎 Century Club (42) 🔥 Unstoppable (5)

Conferences

ICLR (9) NIPS (7) CVPR (6) ICML (6) AAAI (4) ECCV (3) EMNLP (2) ICCV (2) MICCAI (1) UAI (1) WACV (1)

Top co-authors

Bernard Ghanem (22) Philip Torr (19) Philip H.S. Torr (11) Motasem Alfarra (8) Aleksandar Petrov (7) Hasan Abed Al Kader Hammoud (6) Ameya Prabhu (5) Francisco Eiras (4) Mohamed Elhoseiny (3) Christian Schroeder de Witt (3)

Keywords

continual learning (4) adversarial attack (3) sparse representation (3) randomized smoothing (3) certified robustness (3) particle filter (2) memory sampling (2) adversarial defense (2) online learning (2) fourier domain (2) large language model (2) deep neural network (2) adversarial training (2) computational efficiency (2) certified accuracy (2) game theory (1) convex optimization (1) ensemble learning (1) non-convex optimization (1) benchmark evaluation (1)

Papers

Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models ICLR 2025

Shh, don't say that! Domain Certification in LLMs ICLR 2025

Towards Certification of Uncertainty Calibration under Adversarial Attacks ICLR 2025

Mixture of Experts Made Intrinsically Interpretable ICML 2025

Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models ICLR 2025

Detecting LLM Hallucination Through Layer-wise Information Deficiency: Analysis of Ambiguous Prompts and Unanswerable Questions EMNLP 2025

SimCS: Simulation for Domain Incremental Online Continual Segmentation AAAI 2024

Prompting a Pretrained Transformer Can Be a Universal Approximator ICML 2024

Can Large Language Model Agents Simulate Human Trust Behavior? NIPS 2024

No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance NIPS 2024

Universal In-Context Approximation By Prompting Fully Recurrent Models NIPS 2024

Efficient Lifelong Model Evaluation in an Era of Rapid Progress NIPS 2024

Label Delay in Online Continual Learning NIPS 2024

On Pretraining Data Diversity for Self-Supervised Learning ECCV 2024

Model Merging and Safety Alignment: One Bad Model Spoils the Bunch EMNLP 2024

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks ICLR 2024

Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation ICLR 2024

When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations ICLR 2024

Efficient Error Certification for Physics-Informed Neural Networks ICML 2024

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI ICML 2024

Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation ICML 2024

FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging MICCAI 2024

Real-Time Evaluation in Online Continual Learning: A New Hope CVPR 2023

Language Model Tokenizers Introduce Unfairness Between Languages NIPS 2023

Certifying Ensembles: A General Certification Theory with S-Lipschitzness ICML 2023

Computationally Budgeted Continual Learning: What Does Matter? CVPR 2023

RANCER: Non-Axis Aligned Anisotropic Certification With Randomized Smoothing WACV 2023

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? ICCV 2023

Combating Adversaries with Anti-adversaries AAAI 2022

Make Some Noise: Reliable and Efficient Single-Step Adversarial Training NIPS 2022

Data dependent randomized smoothing UAI 2022

DeformRS: Certifying Input Deformations with Randomized Smoothing AAAI 2022

Gabor Layers Enhance Network Robustness ECCV 2020

A Stochastic Derivative Free Optimization Method with Momentum ICLR 2020

A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control AAAI 2020

Deep Layers as Stochastic Solvers ICLR 2019

Analytic Expressions for Probabilistic Moments of PL-DNN With Gaussian Input CVPR 2018

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild ECCV 2018

High Order Tensor Formulation for Convolutional Sparse Coding ICCV 2017

FFTLasso: Large-Scale LASSO in the Fourier Domain CVPR 2017

3D Part-Based Sparse Tracker With Automatic Synchronization and Registration CVPR 2016

In Defense of Sparse Tracking: Circulant Sparse Tracker CVPR 2016