Adel Bibi

Venues

Frequent coauthors

Papers

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

   Wenxuan Zhang

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

   Hazel Kim

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

   Francisco Eiras

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4. MIP against Agent: Malicious Image Patches Hijacking Multimodal OS Agents
   NeurIPS 2025 ·

   Lukas Aichberger

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5. Measuring what Matters: Construct Validity in Large Language Model Benchmarks
   NeurIPS 2025 ·

   Andrew M. Bean

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6. Mixture of Experts Made Intrinsically Interpretable
   ICML 2025 ·

   Xingyi Yang

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7. On the Coexistence and Ensembling of Watermarks
   NeurIPS 2025 ·

   Aleksandar Petrov

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

   Cornelius Emde

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9. Towards Certification of Uncertainty Calibration under Adversarial Attacks
   ICLR 2025 ·

   Cornelius Emde

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10. Can Large Language Model Agents Simulate Human Trust Behavior?
    NeurIPS 2024 ·

    Chengxing Xie

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

    Wenxuan Zhang

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12. Efficient Error Certification for Physics-Informed Neural Networks
    ICML 2024 ·

    Francisco Eiras

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13. Efficient Lifelong Model Evaluation in an Era of Rapid Progress
    NeurIPS 2024 ·

    Ameya Prabhu

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

    Kumail Alhamoud

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

    Tim Franzmeyer

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16. Label Delay in Online Continual Learning
    NeurIPS 2024 ·

    Botos Csaba

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

    Hasan Hammoud

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18. No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
    NeurIPS 2024 ·

    Vishaal Udandarao

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19. On Pretraining Data Diversity for Self-Supervised Learning
    ECCV 2024 ·

    Hasan Abed Al Kader Hammoud

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

    Francisco Eiras

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21. Prompting a Pretrained Transformer Can Be a Universal Approximator
    ICML 2024 ·

    Aleksandar Petrov

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22. Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation
    ECCV 2024 ·

    Francisco Eiras

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23. SimCS: Simulation for Domain Incremental Online Continual Segmentation
    AAAI 2024 ·

    Motasem Alfarra

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24. Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation
    ICML 2024 ·

    Yibo Yang

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25. Universal In-Context Approximation By Prompting Fully Recurrent Models
    NeurIPS 2024 ·

    Aleksandar Petrov

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

    Aleksandar Petrov

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