← Authors

Kristian Kersting

92 papers · 2007–2025 · 19 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (9) πŸ—ΊοΈ Taxonomy Completionist (42) πŸƒ Academic Marathon (18) 🧭 Keyword Pioneer 🌍 Conference Polyglot (19) 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ”¬ Deep Specialist (11) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion πŸ† Grand Slam 🀝 Dynamic Duo (24) πŸ’Ž Century Club (92) ❓ The Questioner (3) πŸš€ Conference Pioneer ⚑ Prolific Year (16) πŸ”₯ Unstoppable (14) πŸ—ƒοΈ Keyword Collector (112) πŸ“ˆ Trend Setter

Conferences

NIPS (14) ICML (10) IJCAI (9) ICLR (9) UAI (8) EMNLP (5) AISTATS (5) PGM (5) CVPR (4) ACL (4) AAAI (4) ICCV (3) JMLR (3) AUTOML (2) ACML (2) NAACL (2) IJCNLP (1) AACL (1) RSS (1)

Top co-authors

Patrick Schramowski (24) Manuel Brack (16) Devendra Singh Dhami (13) Wolfgang Stammer (10) Zhongjie Yu (8) Quentin Delfosse (7) Alejandro Molina (7) Martin Mundt (7) Sriraam Natarajan (7) BjΓΆrn Deiseroth (7)

Research topics

Privacy (1)

Keywords

sum-product network (8) probabilistic circuit (7) large language model (6) gaussian process (4) diffusion model (4) neural network (4) uncertainty quantification (4) probabilistic inference (4) probabilistic model (3) text-to-image synthesis (3) text-to-image generation (3) cross-lingual transfer (3) concept learning (3) relational learning (3) tractable inference (3) bayesian inference (3) scene understanding (3) probabilistic modeling (3) anomaly detection (3) density estimation (3)

Papers

METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding EMNLP 2025
Hyperparameter Optimization via Interacting with Probabilistic Circuits AUTOML 2025
Multilingual Text-to-Image Generation Magnifies Gender Stereotypes ACL 2025
STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond ACL 2025
Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad? ICML 2025
LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models ICML 2025
Where is the Truth? The Risk of Getting Confounded in a Continual World ICML 2025
ART: Adaptive Relation Tuning for Generalized Relation Prediction ICCV 2025
Systems with Switching Causal Relations: A Meta-Causal Perspective ICLR 2025
Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models EMNLP 2025
Credibility-Aware Multimodal Fusion Using Probabilistic Circuits AISTATS 2025
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding ICLR 2025
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning ICLR 2025
Human-in-the-loop or AI-in-the-loop? Automate or Collaborate? AAAI 2025
Scaling Probabilistic Circuits via Data Partitioning UAI 2025
Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint) IJCAI 2024
Learning to Intervene on Concept Bottlenecks ICML 2024
Mechanistic Design and Scaling of Hybrid Architectures ICML 2024
Deep Classifier Mimicry without Data Access AISTATS 2024
DeiSAM: Segment Anything with Deictic Prompting NIPS 2024
T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient Embeddings EMNLP 2024
LEDITS++: Limitless Image Editing using Text-to-Image Models CVPR 2024
Community OSCAR: A Community Effort for Multilingual Web Data EMNLP 2024
Occiglot at WMT24: European Open-source Large Language Models Evaluated on Translation EMNLP 2024
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents NIPS 2024
Neural Concept Binder NIPS 2024
Adaptive Rational Activations to Boost Deep Reinforcement Learning ICLR 2024
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks ICLR 2024
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG ICLR 2024
Graph Neural Networks Need Cluster-Normalize-Activate Modules NIPS 2024
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models NIPS 2024
Bi-Level One-Shot Architecture Search for Probabilistic Time Series Forecasting AUTOML 2024
$Ο‡$SPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains UAI 2024
$Ξ¨$net: Efficient Causal Modeling at Scale PGM 2024
Divergent Token Metrics: Measuring degradation to prune away LLM components – and optimize quantization NAACL 2024
Pix2Code: Learning to Compose Neural Visual Concepts as Programs UAI 2024
ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models ACL 2023
SEGA: Instructing Text-to-Image Models using Semantic Guidance NIPS 2023
Characteristic Circuits NIPS 2023
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction NIPS 2023
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation NIPS 2023
Do Not Marginalize Mechanisms, Rather Consolidate! NIPS 2023
ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation NIPS 2023
Distilling Adversarial Prompts from Safety Benchmarks: Report for the Adversarial Nibbler Challenge AACL 2023
Speaking Multiple Languages Affects the Moral Bias of Language Models ACL 2023
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models CVPR 2023
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis ICCV 2023
Vision Relation Transformer for Unbiased Scene Graph Generation ICCV 2023
ILLUME: Rationalizing Vision-Language Models through Human Interactions ICML 2023
Distilling Adversarial Prompts from Safety Benchmarks: Report for the Adversarial Nibbler Challenge IJCNLP 2023
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference UAI 2023
Probabilistic circuits that know what they don’t know UAI 2023
Neuro-Symbolic Verification of Deep Neural Networks IJCAI 2022
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks IJCAI 2022
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability ICLR 2022
Interactive Disentanglement: Learning Concepts by Interacting With Their Prototype Representations CVPR 2022
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks ICML 2022
Predictive Whittle networks for time series UAI 2022
Explaining Deep Tractable Probabilistic Models: The sum-product network case PGM 2022
Adaptable Adapters NAACL 2022
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations CVPR 2021
Whittle Networks: A Deep Likelihood Model for Time Series ICML 2021
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions AAAI 2021
Leveraging probabilistic circuits for nonparametric multi-output regression UAI 2021
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models NIPS 2021
PadΓ© Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks ICLR 2020
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits ICML 2020
Structured Object-Aware Physics Prediction for Video Modeling and Planning ICLR 2020
Residual Sum-Product Networks PGM 2020
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures PGM 2020
Discriminative Non-Parametric Learning of Arithmetic Circuits PGM 2020
Automatic Bayesian Density Analysis AAAI 2019
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning UAI 2019
Faster Attend-Infer-Repeat with Tractable Probabilistic Models ICML 2019
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs AAAI 2019
Lifted Filtering via Exchangeable Decomposition IJCAI 2018
Efficient Symbolic Integration for Probabilistic Inference IJCAI 2018
Systems AI: A Declarative Learning Based Programming Perspective IJCAI 2018
Stochastic Online Anomaly Analysis for Streaming Time Series IJCAI 2017
Learning Using Unselected Features (LUFe) IJCAI 2016
pyGPs -- A Python Library for Gaussian Process Regression and Classification JMLR 2015
Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation IJCAI 2015
Efficient Lifting of MAP LP Relaxations Using k-Locality AISTATS 2014
Mind the Nuisance: Gaussian Process Classification using Privileged Noise NIPS 2014
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels ACML 2013
Symbolic Dynamic Programming for Continuous State and Observation POMDPs NIPS 2012
Exploration in Relational Domains for Model-based Reinforcement Learning JMLR 2012
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data AISTATS 2012
Lifted Linear Programming AISTATS 2012
Hierarchical Convex NMF for Clustering Massive Data ACML 2010
Integrating Naïve Bayes and FOIL JMLR 2007
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders RSS 2007