Soheil Feizi
89 papers · 2014–2026 · 12 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+14 more ↓ Show less ↑
🗺️ Taxonomy Completionist (107) 🌉 Interdisciplinary Bridge · Silver 🌍 Conference Polyglot · Gold 🏃 Academic Marathon · Half 🐣 Hot Topic Early Bird
🏠
Conference Loyalist
(25)
🔬
Deep Specialist
(23)
🏆
Grand Slam
🤝
Dynamic Duo
(14)
🧬
Topic Evolution
👑
Triple Crown
🏆
Keyword Champion
(11)
⚡
Prolific Year · Prolific
🔥
Unstoppable · Silver
❓
The Questioner
(2)
💎
Century Club · Silver
🌈
Renaissance Researcher
(9)
📈
Trend Setter
🗃️
Keyword Collector
(366)
Venues
Top co-authors
Research topics
Machine Learning
(70)
Artificial Intelligence
(51)
Deep Learning
(49)
Core AI
(47)
Learning Types · Machine Learning
(40)
Optimization & Theory · Machine Learning
(29)
Application Areas
(27)
Learning Types · Deep Learning
(21)
Core Methods
(16)
Models
(15)
Architectures
(14)
Computer Vision
(13)
Analysis
(9)
Techniques
(9)
Optimization & Theory · Deep Learning
(8)
Keywords
adversarial robustness
(21)
image classification
(11)
certified robustness
(11)
adversarial training
(9)
adversarial attack
(8)
neural network
(8)
randomized smoothing
(7)
generative adversarial network
(6)
wasserstein distance
(6)
data poisoning
(5)
large language model
(5)
convolutional neural network
(4)
adversarial defense
(4)
transfer learning
(4)
threat model
(4)
robust optimization
(4)
vision-language model
(4)
deep neural network
(3)
knowledge distillation
(3)
generative model
(3)
Papers
Attacker’s Noise Can Manipulate Your Audio-based LLM in the Real World
EACL 2026
Decomposition-Enhanced Training for Post-Hoc Attributions in Language Models
EACL 2026
Schoenfeld’s Anatomy of Mathematical Reasoning by Language Models
ACL 2026
SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control
CVPR 2026
A Closer Look at Bias and Chain-of-Thought Faithfulness of Large (Vision) Language Models
EMNLP 2025
Almost AI, Almost Human: The Challenge of Detecting AI-Polished Writing
ACL 2025
DyePack: Provably Flagging Test Set Contamination in LLMs Using Backdoors
EMNLP 2025
How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings
ICLR 2025
RePanda: Pandas-powered Tabular Verification and Reasoning
ACL 2025
Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
ICLR 2025
Tool Preferences in Agentic LLMs are Unreliable
EMNLP 2025
Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models
ICLR 2025
Data-Centric Debugging: Mitigating Model Failures via Targeted Image Retrieval
WACV 2024
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP
NeurIPS 2024
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP
EMNLP 2024
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
ICLR 2024
Fast Adversarial Attacks on Language Models In One GPU Minute
ICML 2024
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning
EMNLP 2024
LLM-Check: Investigating Detection of Hallucinations in Large Language Models
NeurIPS 2024
Localizing and Editing Knowledge In Text-to-Image Generative Models
ICLR 2024
Loki: Low-rank Keys for Efficient Sparse Attention
NeurIPS 2024
Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features
AAAI 2024
On Mechanistic Knowledge Localization in Text-to-Image Generative Models
ICML 2024
PRIME: Prioritizing Interpretability in Failure Mode Extraction
ICLR 2024
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
ICLR 2024
Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning
AAAI 2024
Understanding Information Storage and Transfer in Multi-Modal Large Language Models
NeurIPS 2024
Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication
ICLR 2023
CUDA: Convolution-Based Unlearnable Datasets
CVPR 2023
Diffused Redundancy in Pre-trained Representations
NeurIPS 2023
Exploring Geometry of Blind Spots in Vision models
NeurIPS 2023
Goal-Conditioned Q-learning as Knowledge Distillation
AAAI 2023
Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks
ICLR 2023
Identifying Interpretable Subspaces in Image Representations
ICML 2023
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization
ICLR 2023
Run-off Election: Improved Provable Defense against Data Poisoning Attacks
ICML 2023
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
NeurIPS 2023
Temporal Robustness against Data poisoning
NeurIPS 2023
Text-To-Concept (and Back) via Cross-Model Alignment
ICML 2023
Towards Improved Input Masking for Convolutional Neural Networks
ICCV 2023
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes
CVPR 2022
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness
NeurIPS 2022
FOCUS: Familiar Objects in Common and Uncommon Settings
ICML 2022
Hard ImageNet: Segmentations for Objects with Strong Spurious Cues
NeurIPS 2022
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation
ICML 2022
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100
ICLR 2022
Improved techniques for deterministic l2 robustness
NeurIPS 2022
Lethal Dose Conjecture on Data Poisoning
NeurIPS 2022
Policy Smoothing for Provably Robust Reinforcement Learning
ICLR 2022
Provable Adversarial Robustness for Fractional Lp Threat Models
AISTATS 2022
Salient ImageNet: How to discover spurious features in Deep Learning?
ICLR 2022
Segment and Complete: Defending Object Detectors Against Adversarial Patch Attacks With Robust Patch Detection
CVPR 2022
Toward Efficient Robust Training against Union of ℓ_p Threat Models
NeurIPS 2022
Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
ICLR 2021
Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
ICLR 2021
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
AISTATS 2021
Improved, Deterministic Smoothing for L_1 Certified Robustness
ICML 2021
Improving Deep Learning Interpretability by Saliency Guided Training
NeurIPS 2021
Influence Functions in Deep Learning Are Fragile
ICLR 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training
ICCV 2021
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
ICLR 2021
Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings
ICCV 2021
Skew Orthogonal Convolutions
ICML 2021
Understanding Over-parameterization in Generative Adversarial Networks
ICLR 2021
Unsupervised anomaly detection with adversarial mirrored autoencoders
UAI 2021
Winning Lottery Tickets in Deep Generative Models
AAAI 2021
Adversarially Robust Distillation
AAAI 2020
Adversarial Robustness of Flow-Based Generative Models
AISTATS 2020
Benchmarking Deep Learning Interpretability in Time Series Predictions
NeurIPS 2020
Certifying Confidence via Randomized Smoothing
NeurIPS 2020
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness
ICML 2020
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
NeurIPS 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks
NeurIPS 2020
Maximum Likelihood Embedding of Logistic Random Dot Product Graphs
AAAI 2020
On Second-Order Group Influence Functions for Black-Box Predictions
ICML 2020
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation
AAAI 2020
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation
NeurIPS 2020
Second-Order Provable Defenses against Adversarial Attacks
ICML 2020
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks
AISTATS 2020
Are adversarial examples inevitable?
ICLR 2019
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
ICML 2019
Functional Adversarial Attacks
NeurIPS 2019
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks
NeurIPS 2019
Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation
ICCV 2019
Quantum Wasserstein Generative Adversarial Networks
NeurIPS 2019
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
ICML 2019
Porcupine Neural Networks: Approximating Neural Network Landscapes
NeurIPS 2018
Tensor Biclustering
NeurIPS 2017
Biclustering Using Message Passing
NeurIPS 2014