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Jannik Kossen
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2020 – today
- 2024
- [j2]Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn, Yarin Gal:
Detecting hallucinations in large language models using semantic entropy. Nat. 630(8017): 625-630 (2024) - [c6]Jannik Kossen, Yarin Gal, Tom Rainforth:
In-Context Learning Learns Label Relationships but Is Not Conventional Learning. ICLR 2024 - [i12]Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen:
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities. CoRR abs/2405.20003 (2024) - [i11]Andrew Jesson, Nicolas Beltran-Velez, Quentin Chu, Sweta Karlekar, Jannik Kossen, Yarin Gal, John P. Cunningham, David M. Blei:
Estimating the Hallucination Rate of Generative AI. CoRR abs/2406.07457 (2024) - [i10]Jannik Kossen, Jiatong Han, Muhammed Razzak, Lisa Schut, Shreshth A. Malik, Yarin Gal:
Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs. CoRR abs/2406.15927 (2024) - [i9]Benedict Aaron Tjandra, Muhammed Razzak, Jannik Kossen, Kunal Handa, Yarin Gal:
Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy. CoRR abs/2410.17234 (2024) - 2023
- [j1]Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave:
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. Trans. Mach. Learn. Res. 2023 (2023) - [c5]Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou:
Three Towers: Flexible Contrastive Learning with Pretrained Image Models. NeurIPS 2023 - [i8]Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou:
Three Towers: Flexible Contrastive Learning with Pretrained Image Models. CoRR abs/2305.16999 (2023) - [i7]Jannik Kossen, Tom Rainforth, Yarin Gal:
In-Context Learning in Large Language Models Learns Label Relationships but Is Not Conventional Learning. CoRR abs/2307.12375 (2023) - 2022
- [c4]Jannik Kossen, Sebastian Farquhar, Yarin Gal, Thomas Rainforth:
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation. NeurIPS 2022 - [i6]Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth:
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation. CoRR abs/2202.06881 (2022) - [i5]Andreas Kirsch, Jannik Kossen, Yarin Gal:
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling. CoRR abs/2205.08766 (2022) - [i4]Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave:
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. CoRR abs/2211.05039 (2022) - 2021
- [c3]Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth:
Active Testing: Sample-Efficient Model Evaluation. ICML 2021: 5753-5763 - [c2]Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal:
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. NeurIPS 2021: 28742-28756 - [i3]Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth:
Active Testing: Sample-Efficient Model Evaluation. CoRR abs/2103.05331 (2021) - [i2]Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Tom Rainforth, Yarin Gal:
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. CoRR abs/2106.02584 (2021) - 2020
- [c1]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020
2010 – 2019
- 2019
- [i1]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR abs/1910.02425 (2019)
Coauthor Index
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