Kristian Kersting

papers in the register

1. Birds of a Feather Reason Together: Gestalt Grouping Meets Neuro-Symbolic Inference
   UAI · 2026lab-submitted
2. SLR: Automated Synthesis for Scalable Logical Reasoning.
   ACL · 2026
3. Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning.
   ACL · 2026
4. Finding DoRI: Discovery of Retained Images in Diffusion Models
   ICML · 2026lab-submitted
5. Hybrid Many-Objective Optimization in Probabilistic Mission Design for Compliant and Effective UAV Routing
   ACM Journal on Autonomous Transportation Systems · 2025
   Probabilistic logicRouting (electronic design automation)Computer science
6. Where is the Truth? The Risk of Getting Confounded in a Continual World.
   ICML · 2025
7. Systems with Switching Causal Relations: A Meta-Causal Perspective.
   ICLR · 2025
8. STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond.
   ACL · 2025
9. ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding.
   ICLR · 2025
10. Credibility-Aware Multimodal Fusion Using Probabilistic Circuits.
    AISTATS · 2025
11. Scaling Probabilistic Circuits via Data Partitioning.
    UAI · 2025
12. METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding.
    EMNLP · 2025
13. Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?
    ICML · 2025
14. EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition.
    NeurIPS · 2025
15. The Constitutional Filter: Bayesian Estimation of Compliant Agents
    IROS · 2025
    Artificial intelligenceComputer scienceMachine learningParticle filter
16. Core Tokensets for Data-Efficient Sequential Training of Transformers.
    ICCV · 2025
17. BlendRL: A Framework for Merging Symbolic and Neural Policy Learning.
    ICLR · 2025
18. How to Train Your Text-to-Image Model: Evaluating Design Choices for Synthetic Training Captions.
    ICCV · 2025
19. LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models.
    ICML · 2025
20. Human-in-the-loop or AI-in-the-loop? Automate or Collaborate?
    AAAI · 2025
    Human-in-the-loopLoop (graph theory)Computer science
21. Measuring and Guiding Monosemanticity.
    NeurIPS · 2025
22. Multilingual Text-to-Image Generation Magnifies Gender Stereotypes.
    ACL · 2025
23. Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models.
    EMNLP · 2025
24. Problem Solving Through Human–AI Preference-based Cooperation
    Computational Linguistics · 2025
    Computer sciencePreferenceArtificial intelligenceCognitive science
25. Probabilistic Mission Design for Neuro-Symbolic Unmanned Aircraft Systems
    IEEE Transactions on Intelligent Transportation Systems · 2025
    Probabilistic logicComputer scienceArtificial intelligence
26. ART: Adaptive Relation Tuning for Generalized Relation Prediction
    ICCV · 2025
    Relation (database)Computer scienceFocus (optics)Artificial intelligence
27. Divergent Token Metrics: Measuring degradation to prune away LLM components - and optimize quantization.
    NAACL · 2024
28. Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG.
    ICLR · 2024
29. Neural Concept Binder.
    NeurIPS · 2024
30. LEDITS++: Limitless Image Editing Using Text-to-Image Models
    CVPR · 2024
    Image (mathematics)Computer scienceImage editingArtificial intelligence
31. Mechanistic Design and Scaling of Hybrid Architectures.
    ICML · 2024
32. Pix2Code: Learning to Compose Neural Visual Concepts as Programs.
    UAI · 2024
33. Towards Probabilistic Clearance, Explanation and Optimization
    2024
    Probabilistic logicComputer science
34. Does CLIP Know My Face?
    Journal of Artificial Intelligence Research · 2024
    Computer scienceInferenceVariety (cybernetics)Identity (music)
35. “Do Not Disturb My Circles!” Identifying the Type of Counterfactual at Hand (Short Paper)
    Lecture notes in computer science · 2024
    Counterfactual thinkingComputer scienceType (biology)Artificial intelligence
36. Structural causal models reveal confounder bias in linear program modelling
    Machine Learning · 2024
    Adversarial systemMathematical proofComputer scienceFormalism (music)
37. Auditing and instructing text-to-image generation models on fairness
    AI and Ethics · 2024
    Generative grammarComputer scienceSoftware deploymentImage (mathematics)
38. APT: Alarm Prediction Transformer
    Expert Systems with Applications · 2024
    Computer scienceALARMTransformerArtificial intelligence
39. Multimodal transformer for early alarm prediction
    Engineering Applications of Artificial Intelligence · 2024
    Computer scienceALARMTransformerArtificial intelligence
40. Representation Matters for Mastering Chess: Improved Feature Representation in AlphaZero Outperforms Switching to Transformers
    Frontiers in artificial intelligence and applications · 2024
    Representation (politics)TransformerArtificial intelligenceComputer science
41. Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning
    TUbilio (Technical University of Darmstadt) · 2024
    Argumentation theoryArgument (complex analysis)Computer scienceArtificial intelligence
42. We Should Care about Explaining Even Linear Programs
    2024
    Computer scienceAttributionRelevance (law)Solver
43. DeiSAM: Segment Anything with Deictic Prompting.
    NeurIPS · 2024
44. Causality in Flux: Continual Adaptation of Causal Knowledge via Evidence Matching.
    AAAI · 2024
45. Adaptive Rational Activations to Boost Deep Reinforcement Learning.
    ICLR · 2024
46. Graph Neural Networks Need Cluster-Normalize-Activate Modules.
    NeurIPS · 2024
47. T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient Embeddings.
    EMNLP · 2024
48. χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains.
    UAI · 2024
49. Deep Classifier Mimicry without Data Access.
    AISTATS · 2024
50. Learning to Intervene on Concept Bottlenecks.
    ICML · 2024
51. Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents.
    NeurIPS · 2024
52. Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks.
    ICLR · 2024
53. Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images
    Remote Sensing · 2024
    Pipeline transportComputer sciencePipeline (software)Remote sensing
54. Exploiting Cultural Biases via Homoglyphs inText-to-Image Synthesis (Abstract Reprint).
    IJCAI · 2024
55. Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models.
    NeurIPS · 2024
56. Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference.
    UAI · 2023
57. Never Ending Reasoning and Learning: Opportunities and Challenges.
    AAAI · 2023
58. One Explanation Does Not Fit XIL.
    ICLR · 2023
59. Do Not Marginalize Mechanisms, Rather Consolidate!
    NeurIPS · 2023
60. Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis.
    ICCV · 2023
61. Characteristic Circuits.
    NeurIPS · 2023
62. SEGA: Instructing Text-to-Image Models using Semantic Guidance.
    NeurIPS · 2023
63. Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction.
    NeurIPS · 2023
64. Speaking Multiple Languages Affects the Moral Bias of Language Models.
    ACL · 2023
65. ILLUME: Rationalizing Vision-Language Models through Human Interactions.
    ICML · 2023
66. MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation.
    NeurIPS · 2023
67. Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models.
    CVPR · 2023
68. ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation.
    NeurIPS · 2023
69. Vision Relation Transformer for Unbiased Scene Graph Generation.
    ICCV · 2023
70. Probabilistic circuits that know what they don't know.
    UAI · 2023
71. Predictive Whittle networks for time series.
    UAI · 2022
72. Adaptable Adapters.
    NAACL · 2022
73. Neuro-Symbolic Verification of Deep Neural Networks.
    IJCAI · 2022
74. Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations.
    CVPR · 2022
75. To Trust or Not To Trust Prediction Scores for Membership Inference Attacks.
    IJCAI · 2022
76. CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability.
    ICLR · 2022
77. Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks.
    ICML · 2022
78. Whittle Networks: A Deep Likelihood Model for Time Series.
    ICML · 2021
79. Leveraging probabilistic circuits for nonparametric multi-output regression.
    UAI · 2021
80. Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions.
    AAAI · 2021
81. Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.
    NeurIPS · 2021
82. Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations.
    CVPR · 2021
83. Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks.
    ICLR · 2020
84. Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits.
    ICML · 2020
85. Structured Object-Aware Physics Prediction for Video Modeling and Planning.
    ICLR · 2020
86. Faster Attend-Infer-Repeat with Tractable Probabilistic Models.
    ICML · 2019
87. Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.
    AAAI · 2019
88. Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning.
    UAI · 2019
89. Automatic Bayesian Density Analysis.
    AAAI · 2019
90. Lifted Filtering via Exchangeable Decomposition.
    IJCAI · 2018
91. Systems AI: A Declarative Learning Based Programming Perspective.
    IJCAI · 2018
92. Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives.
    ICRA · 2018
93. Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains.
    AAAI · 2018
94. Efficient Symbolic Integration for Probabilistic Inference.
    IJCAI · 2018
95. Core Dependency Networks.
    AAAI · 2018
96. Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks.
    AAAI · 2018
97. Lifted Inference for Convex Quadratic Programs.
    AAAI · 2017
98. Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.
    AAAI · 2017
99. Stochastic Online Anomaly Analysis for Streaming Time Series.
    IJCAI · 2017
100. The Symbolic Interior Point Method.
     AAAI · 2017
101. RELOOP: A Python-Embedded Declarative Language for Relational Optimization.
     AAAI · 2016
102. Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.
     AAAI · 2016
103. Learning Using Unselected Features (LUFe).
     IJCAI · 2016
104. Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation.
     IJCAI · 2015
105. Parameterizing the Distance Distribution of Undirected Networks.
     UAI · 2015
106. Equitable Partitions of Concave Free Energies.
     UAI · 2015
107. Mind the Nuisance: Gaussian Process Classification using Privileged Noise.
     NeurIPS · 2014
108. Lifting Relational MAP-LPs Using Cluster Signatures.
     AAAI · 2014
109. Power Iterated Color Refinement.
     AAAI · 2014
110. Preface.
     AAAI · 2014
111. A Deeper Empirical Analysis of CBP Algorithm: Grounding Is the Bottleneck.
     AAAI · 2014
112. Lifted Message Passing as Reparametrization of Graphical Models.
     UAI · 2014
113. Relational Logistic Regression: The Directed Analog of Markov Logic Networks.
     AAAI · 2014
114. Efficient Lifting of MAP LP Relaxations Using k-Locality.
     AISTATS · 2014
115. Lifted Inference via k-Locality.
     AAAI · 2013
116. MapReduce Lifting for Belief Propagation.
     AAAI · 2013
117. Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP.
     AAAI · 2013
118. Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text.
     AAAI · 2013
119. Symbolic Dynamic Programming for Continuous State and Observation POMDPs.
     NeurIPS · 2012
120. Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images.
     AAAI · 2012
121. Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants.
     UAI · 2012
122. Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter.
     IJCAI · 2011
123. Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.
     IJCAI · 2011
124. Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation.
     AAAI · 2011
125. Learning to hash logistic regression for fast 3D scan point classification.
     IROS · 2010
126. Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
     AAAI · 2010
127. Lifted Message Passing for Satisfiability.
     AAAI · 2010
128. Informed Lifting for Message-Passing.
     AAAI · 2010
129. Symbolic Dynamic Programming for First-order POMDPs.
     AAAI · 2010
130. Multi-Relational Learning with Gaussian Processes.
     IJCAI · 2009
131. Counting Belief Propagation.
     UAI · 2009
132. Generalized First Order Decision Diagrams for First Order Markov Decision Processes.
     IJCAI · 2009
133. Social Network Mining with Nonparametric Relational Models.
     KDD · 2008
134. Learning predictive terrain models for legged robot locomotion.
     IROS · 2008
135. Non-parametric policy gradients: a unified treatment of propositional and relational domains.
     ICML · 2008
136. Lifted Probabilistic Inference with Counting Formulas.
     AAAI · 2008
137. Most likely heteroscedastic Gaussian process regression.
     ICML · 2007
138. Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.
     RSS · 2007
139. Learning Relational Navigation Policies.
     IROS · 2006
140. Robust 3D Scan Point Classification using Associative Markov Networks.
     ICRA · 2006
141. Towards Learning Stochastic Logic Programs from Proof-Banks.
     AAAI · 2005
142. "Say EM" for Selecting Probabilistic Models for Logical Sequences.
     UAI · 2005
143. nFOIL: Integrating Naïve Bayes and FOIL.
     AAAI · 2005
144. Bellman goes relational.
     ICML · 2004

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