default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKaren Ullrich
Person information
- affiliation: Meta, Menlo Park, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
2020 – today
- 2026
[i31]Jamelle Watson-Daniels, Himaghna Bhattacharjee, Skyler Wang, Brandon Handoko, Antonio Li, Anaelia Ovalle, Mahesh Pasupuleti, Candace Ross, Vidya Sarma, Arjun Subramonian, Karen Ullrich, Will van der Vaart, Yijing Xin, Maximilian Nickel:
SCRuB: Social Concept Reasoning under Rubric-Based Evaluation. CoRR abs/2605.06444 (2026)- 2025
- [j4]Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin:
On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. 2025 (2025) - [c17]Matthew J. Muckley, Marton Havasi, Jakob Verbeek, Karen Ullrich:
Architecture Optimizations for Improving Neural Image Compression Compute Complexity. DCC 2025: 3-12 - [c16]Daniel Severo, Jingtong Su, Anji Liu
, Jeff Johnson, Brian Karrer, Guy Van den Broeck, Matthew J. Muckley, Karen Ullrich:
Enhancing and Evaluating Probabilistic Circuits for High-Resolution Lossless Image Compression. DCC 2025: 253-262 - [c15]Revant Teotia, Candace Ross, Karen Ullrich, Sumit Chopra, Adriana Romero-Soriano, Melissa Hall, Matthew J. Muckley:
DIMCIM: A Quantitative Evaluation Framework for Default-Mode Diversity and Generalization in Text-to-Image Generative Models. ICCV 2025: 16431-16440 - [c14]Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. ICLR 2025 - [c13]Yonathan Efroni, Ben Kretzu, Daniel Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich:
Aligned Multi Objective Optimization. ICML 2025 - [i30]Daniel Severo, Giuseppe Ottaviano, Matthew J. Muckley, Karen Ullrich, Matthijs Douze:
Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search. CoRR abs/2501.10479 (2025) - [i29]Yonathan Efroni, Ben Kertzu, Daniel Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich:
Aligned Multi Objective Optimization. CoRR abs/2502.14096 (2025) - [i28]Revant Teotia, Candace Ross, Karen Ullrich, Sumit Chopra, Adriana Romero-Soriano, Melissa Hall, Matthew J. Muckley:
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models. CoRR abs/2506.05108 (2025) - [i27]Jingtong Su, Julia Kempe, Karen Ullrich:
From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers. CoRR abs/2506.17052 (2025) - [i26]Ben Kretzu, Karen Ullrich, Yonathan Efroni:
Simple Optimizers for Convex Aligned Multi-Objective Optimization. CoRR abs/2509.05811 (2025) - [i25]Shomik Jain, Jack Lanchantin, Maximilian Nickel, Karen Ullrich, Ashia Wilson, Jamelle Watson-Daniels:
LLM Output Homogenization is Task Dependent. CoRR abs/2509.21267 (2025) - [i24]Jingtong Su, Jianyu Zhang, Karen Ullrich, Léon Bottou, Mark Ibrahim:
A Single Character can Make or Break Your LLM Evals. CoRR abs/2510.05152 (2025) - [i23]Nikolaos Tsilivis, Eran Malach, Karen Ullrich, Julia Kempe:
How Reinforcement Learning After Next-Token Prediction Facilitates Learning. CoRR abs/2510.11495 (2025) - [i22]Karen Ullrich, Jingtong Su, Claudia Shi, Arjun Subramonian, Amir Bar, Ivan Evtimov, Nikolaos Tsilivis, Randall Balestriero, Julia Kempe, Mark Ibrahim:
OpenApps: Simulating Environment Variations to Measure UI-Agent Reliability. CoRR abs/2511.20766 (2025) - [i21]Buu Phan, Ashish Khisti, Karen Ullrich:
Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation. CoRR abs/2512.14954 (2025) - [i20]Anaelia Ovalle, Candace Ross, Sebastian Ruder, Adina Williams, Karen Ullrich, Mark Ibrahim, Levent Sagun:
Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages. CoRR abs/2512.22712 (2025) - 2024
- [j3]Julius Berner, Lorenz Richter, Karen Ullrich:
An optimal control perspective on diffusion-based generative modeling. Trans. Mach. Learn. Res. 2024 (2024) - [c12]Da Ju, Karen Ullrich, Adina Williams:
Are Female Carpenters like Blue Bananas? A Corpus Investigation of Occupation Gender Typicality. ACL (Findings) 2024: 4254-4274 - [c11]Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison:
End-To-End Causal Effect Estimation from Unstructured Natural Language Data. NeurIPS 2024 - [c10]Jingtong Su, Julia Kempe, Karen Ullrich:
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs. NeurIPS 2024 - [i19]Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin:
On the Challenges and Opportunities in Generative AI. CoRR abs/2403.00025 (2024) - [i18]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i17]Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Understanding and Mitigating Tokenization Bias in Language Models. CoRR abs/2406.16829 (2024) - [i16]Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison:
End-To-End Causal Effect Estimation from Unstructured Natural Language Data. CoRR abs/2407.07018 (2024) - [i15]Jingtong Su, Julia Kempe, Karen Ullrich:
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs. CoRR abs/2408.01420 (2024) - [i14]Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. CoRR abs/2410.09303 (2024) - [i13]Melissa Hall, Oscar Mañas, Reyhane Askari Hemmat, Mark Ibrahim, Candace Ross, Pietro Astolfi, Tariq Berrada Ifriqi, Marton Havasi, Yohann Benchetrit, Karen Ullrich, Carolina Braga, Abhishek Charnalia, Maeve Ryan, Mike Rabbat, Michal Drozdzal, Jakob Verbeek, Adriana Romero-Soriano:
EvalGIM: A Library for Evaluating Generative Image Models. CoRR abs/2412.10604 (2024) - 2023
- [j2]Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Hervé Jégou:
Image Compression with Product Quantized Masked Image Modeling. Trans. Mach. Learn. Res. 2023 (2023) - [c9]Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich, Hervé Jégou, Jakob Verbeek:
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models. ICML 2023: 25426-25443 - [i12]Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich, Hervé Jégou, Jakob Verbeek:
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models. CoRR abs/2301.11189 (2023) - 2022
- [j1]Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich:
Compressing Multisets With Large Alphabets. IEEE J. Sel. Areas Inf. Theory 3(4): 605-615 (2022) - [c8]Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich:
Compressing Multisets with Large Alphabets. DCC 2022: 322-331 - [i11]Julius Berner, Lorenz Richter, Karen Ullrich:
An optimal control perspective on diffusion-based generative modeling. CoRR abs/2211.01364 (2022) - [i10]Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Hervé Jégou:
Image Compression with Product Quantized Masked Image Modeling. CoRR abs/2212.07372 (2022) - [i9]Ricky T. Q. Chen, Matthew Le, Matthew J. Muckley, Maximilian Nickel, Karen Ullrich:
Latent Discretization for Continuous-time Sequence Compression. CoRR abs/2212.13659 (2022) - 2021
- [c7]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML 2021: 9136-9147 - [c6]Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison:
Lossy Compression for Lossless Prediction. NeurIPS 2021: 14014-14028 - [i8]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR abs/2102.11086 (2021) - [i7]Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison:
Lossy Compression for Lossless Prediction. CoRR abs/2106.10800 (2021) - [i6]Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich:
Compressing Multisets with Large Alphabets. CoRR abs/2107.09202 (2021) - 2020
- [i5]Karen Ullrich, Fabio Viola, Danilo Jimenez Rezende:
Neural Communication Systems with Bandwidth-limited Channel. CoRR abs/2003.13367 (2020)
2010 – 2019
- 2019
- [c5]Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling:
Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem. UAI 2019: 399-411 - [i4]Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling:
Differentiable probabilistic models of scientific imaging with the Fourier slice theorem. CoRR abs/1906.07582 (2019) - 2017
- [c4]Karen Ullrich, Edward Meeds, Max Welling:
Soft Weight-Sharing for Neural Network Compression. ICLR (Poster) 2017 - [c3]Eelco van der Wel, Karen Ullrich:
Optical Music Recognition with Convolutional Sequence-to-Sequence Models. ISMIR 2017: 731-737 - [c2]Christos Louizos, Karen Ullrich, Max Welling:
Bayesian Compression for Deep Learning. NIPS 2017: 3288-3298 - [i3]Karen Ullrich, Edward Meeds, Max Welling:
Soft Weight-Sharing for Neural Network Compression. CoRR abs/1702.04008 (2017) - [i2]Christos Louizos, Karen Ullrich, Max Welling:
Bayesian Compression for Deep Learning. CoRR abs/1705.08665 (2017) - [i1]Eelco van der Wel, Karen Ullrich:
Optical Music Recognition with Convolutional Sequence-to-Sequence Models. CoRR abs/1707.04877 (2017) - 2014
- [c1]Karen Ullrich, Jan Schlüter, Thomas Grill:
Boundary Detection in Music Structure Analysis using Convolutional Neural Networks. ISMIR 2014: 417-422
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-06-09 23:02 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated, funded, and maintained by:
Schloss Dagstuhl - Leibniz Center for Informatics is a member of the Leibniz Association and is funded by the federal government of Germany and the states of Germany, especially Saarland and Rhineland‑Palatinate.
