Golnoosh Farnadi
23 papers · 2015–2026 · 10 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (9) 🏃 Academic Marathon (10) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (6)
🧭
Keyword Pioneer
🏃
Academic Marathon
(10)
🏆
Grand Slam
👑
Triple Crown
🗃️
Keyword Collector
(103)
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Prolific Year
(7)
🚀
Conference Pioneer
💎
Century Club
(20)
📈
Trend Setter
❓
The Questioner
(2)
Conferences
AAAI (9)
EACL (3)
ACL (2)
ICLR (2)
NIPS (2)
EMNLP (1)
ICCV (1)
ICML (1)
IJCAI (1)
NAACL (1)
Top co-authors
Research topics
Keywords
large language model
(5)
individual fairness
(3)
structural causal model
(3)
causal inference
(3)
optimal transport
(2)
machine unlearning
(2)
hallucination detection
(2)
distributionally robust optimization
(2)
combinatorial optimization
(2)
adversarial robustness
(1)
factual accuracy
(1)
wasserstein distance
(1)
cross-lingual transfer
(1)
model evaluation
(1)
uncertainty quantification
(1)
hyperparameter optimization
(1)
differential privacy
(1)
model safety
(1)
minimax optimization
(1)
convex optimization
(1)
Papers
Multilingual Amnesia: On the Transferability of Unlearning in Multilingual LLMs
EACL 2026
Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework
EACL 2026
Rethinking Hallucinations: Correctness, Consistency, and Prompt Multiplicity
EACL 2026
REVIVING YOUR MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing
EMNLP 2025
Erasing More Than Intended? How Concept Erasure Degrades the Generation of Non-Target Concepts
ICCV 2025
Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset
NAACL 2025
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy
AAAI 2025
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
AAAI 2025
What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models
ICLR 2025
Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training
ACL 2025
From Representational Harms to Quality-of-Service Harms: A Case Study on Llama 2 Safety Safeguards
ACL 2024
Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness
NIPS 2024
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces
AAAI 2024
Promoting Fair Vaccination Strategies through Influence Maximization: A Case Study on COVID-19 Spread
AAAI 2024
Learning to Build Solutions in Stochastic Matching Problems Using Flows (Student Abstract)
AAAI 2024
Balancing Act: Constraining Disparate Impact in Sparse Models
ICLR 2024
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
ICML 2024
Individual Fairness in Kidney Exchange Programs
AAAI 2021
BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic
AAAI 2020
Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns
AAAI 2020
Counterexample-Guided Learning of Monotonic Neural Networks
NIPS 2020
Lifted Hinge-Loss Markov Random Fields
AAAI 2019
Statistical Relational Learning Towards Modelling Social Media Users
IJCAI 2015