Reading Group
- Summer Semester 2023
Meta-Learning the Inductive Biases of Simple Neural CircuitsWilliam Dorrell, Maria Yuffa, Peter Latham
Dopamine and temporal difference learning - A fruitful relationship between neuroscience and AIWill Dabney, Zeb Kurth-Nelson
Pattern-Based Music Generation with Wasserstein Autoencoders and PRC DescriptionsValentijn Borghuis, Luca Angioloni, Lorenzo Brusci, Paolo Frasconi
Bytes is all you needMaxwell Horton, Sachin Mehta, Ali Farhadi, Mohammad Rastegari
Masked Autoencoders Are Scalable Vision LearnersKaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár et al.
- Winter Semester 2023/24
Human-level Control through Deep Reinforcement LearningVolodymyr Mnih, K. Kavukcuoglu, David Silver, Andrei A. Rusu, J. Veness et al.
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Dueling Network Architectures for Deep Reinforcement LearningZiyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot et al.
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Deep Reinforcement Learning with Double Q-learningHado van Hasselt, Arthur Guez, David Silver
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Prioritized Experience ReplayTom Schaul, John Quan, Ioannis Antonoglou, David Silver
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
A Distributional Perspective on Reinforcement LearningMarc G. Bellemare, Will Dabney, Rémi Munos
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Noisy Networks for ExplorationMeire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Ian Osband et al.
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Rainbow: Combining Improvements in Deep Reinforcement LearningMatteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski et al.
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
Agent57: Outperforming the Atari Human BenchmarkAdrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi et al.
Hosted by Jarek Liesen. Introduction to deep reinforcement learning through exploration of many relevant and foundational papers.
RL-Duet - Online Music Accompaniment Generation Using Deep Reinforcement LearningNan Jiang, Sheng Jin, Zhiyao Duan, Changshui Zhang
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
Neural Discrete Representation LearningAaron van den Oord, Oriol Vinyals, Koray Kavukcuoglu
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
Jukebox A Generative Model for MusicPrafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford et al.
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
High Fidelity Neural Audio CompressionAlexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
MusicLM: Generating Music From TextAndrea Agostinelli, Timo I. Denk, Zalán Borsos, Jesse Engel, Mauro Verzetti et al.
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
MT3 Multi-Task Multitrack Music TranscriptionJosh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, Jesse Engel
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
Voicebox: Text-Guided Multilingual Universal Speech Generation at ScaleMatthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari et al.
Hosted by Leo Pinetzki. We explore many audio-related papers at the intersection of AI and sound.
- Summer Semester 2024
2 papers: Intriguing Properties of Contrastive Losses, Bootstrap your own latent: A new approach to self-supervised LearningReading group session
Hosted by Jakob Hackstein. Self-supervised learning is highly effective for learning representations from unlabeled data.
2 papers: Emerging Properties in Self-Supervised Vision Transformers, Vision Transformers Need RegistersReading group session
Hosted by Jakob Hackstein. Self-supervised learning is highly effective for learning representations from unlabeled data.
2 papers: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, What do Self Supervised Vision Transformers Learn?Reading group session
Hosted by Jakob Hackstein. Self-supervised learning is highly effective for learning representations from unlabeled data.
2 papers: Revealing the Dark Secrets of Masked Image Modeling, Can We Break Free from Strong Data Augmentations in Self-Supervised Learning?Reading group session
Hosted by Jakob Hackstein. Self-supervised learning is highly effective for learning representations from unlabeled data.
2 papers: Stochastic Gradient Descend, Adding Gradient Noise Improves Learning for Very Deep NetworksReading group session
Hosted by Jarek Liesen. We read papers about optimizers and their properties to learn how to optimize even further.
2 papers: On the importance of initialization and momentum in deep learning, Adam: A Method for Stochastic OptimizationReading group session
Hosted by Jarek Liesen. We read papers about optimizers and their properties to learn how to optimize even further.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
- Winter Semester 2024/25
Language Models are Few-Shot Learners, Chapter 3Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
A Formal Perspective on Byte-Pair EncodingVilém Zouhar, Clara Meister, Juan Luis Gastaldi, Li Du, Tim Vieira et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Training Compute-Optimal Large Language ModelsJordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model ParallelismMohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Training language models to follow instructions with human feedbackLong Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Training Language Models to Self-Correct via Reinforcement LearningAviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, JD Co-Reyes et al.
Hosted by Raphael Reinauer. We explore the basics of natural language processing and the transformer architecture, scaling language models, modern training techniques, and self-improvement.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
A Mathematical Framework for Transformer CircuitsNelson Elhage, Neel Nanda, Catherine Olsson, Tom Henighan†, Nicholas Joseph† et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Toy Models of SuperpositionNelson Elhage, Tristan Hume, Catherine Olsson, Nicholas Schiefer, Tom Henighan et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Towards Monosemanticity: Decomposing Language Models With Dictionary LearningTrenton Bricken, Adly Templeton, Joshua Batson, Brian Chen, Adam Jermyn et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Refusal in Language Models Is Mediated by a Single DirectionAndy Arditi, Oscar Obeso, Aaquib Syed, Daniel Paleka, Nina Panickssery et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 SonnetAdly Templeton, Tom Conerly, Jonathan Marcus, Jack Lindsey, Trenton Bricken et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Efficient Dictionary Learning with Switch Sparse AutoencodersAnish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schroeder de Witt
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Monet: Mixture of Monosemantic Experts for TransformersJungwoo Park, Young Jin Ahn, Kee-Eung Kim, Jaewoo Kang
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language ModelsSamuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov, David Bau et al.
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Transcoders Find Interpretable LLM Feature CircuitsJacob Dunefsky, Philippe Chlenski, Neel Nanda
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter DecompositionDan Braun, Lucius Bushnaq, Stefan Heimersheim, Jake Mendel, Lee Sharkey
Hosted by Lorenz Hufe. A deep dive into understanding the internal mechanisms of language models.
Location: MAR 0.015, TU Berlin (Marchstraße 23, 10587 Berlin)
Time: Every Monday, 7pm
- Summer Semester 2025
A foundation model for clinical-grade computational pathology and rare cancers detectionEugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
A visual-language foundation model for computational pathologyMing Y. Lu, Bowen Chen, Drew F. K. Williamson, Richard J. Chen, Ivy Liang et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Transmil: Transformer based Correlated Multiple Instance Learning for Whole Slide Image ClassificationZhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
A multimodal generative AI copilot for human pathologyMing Y. Lu, Bowen Chen, Drew F. K. Williamson, Richard J. Chen, Melissa Zhao et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised LearningRichard J. Chen, Chengkuan Chen, Yicong Li, Tiffany Y. Chen, Andrew D. Trister et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
PRISM: A Multi-Modal Generative Foundation Model for Slide-Level HistopathologyGeorge Shaikovski, Adam Casson, Kristen Severson, Eric Zimmermann, Yi Kan Wang et al.
Hosted by Tom Neuhäuser. A deep dive into the world of multimodal foundation models for histopathology.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Neural Message Passing for Quantum ChemistryJustin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, George E. Dahl
Hosted by Gregor Lied. This reading group investigated the theoretical foundations and architectural design space of Geometric Graph Neural Networks for 3D atomic systems.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Directional Message Passing for Molecular GraphsJohannes Gasteiger, Janek Groß, Stephan Günnemann
Hosted by Gregor Lied. This reading group investigated the theoretical foundations and architectural design space of Geometric Graph Neural Networks for 3D atomic systems.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
E(n) Equivariant Graph Neural NetworksVictor Garcia Satorras, Emiel Hoogeboom, Max Welling
Hosted by Gregor Lied. This reading group investigated the theoretical foundations and architectural design space of Geometric Graph Neural Networks for 3D atomic systems.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
ForceNet: A Graph Neural Network for Large-Scale Quantum CalculationsWeihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram et al.
Hosted by Gregor Lied. This reading group investigated the theoretical foundations and architectural design space of Geometric Graph Neural Networks for 3D atomic systems.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
On the Expressive Power of Geometric Graph Neural NetworksChaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Liò
Hosted by Gregor Lied. This reading group investigated the theoretical foundations and architectural design space of Geometric Graph Neural Networks for 3D atomic systems.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
- Winter Semester 2025/26
U-Net: Convolutional Networks for Biomedical Image SegmentationOlaf Ronneberger, Philipp Fischer, Thomas Brox
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Biologically Guided Variational Inference for Interpretable Multimodal Single-Cell Integration and Mechanistic DiscoveryLucas Arnoldt, Julius Upmeier zu Belzen, Luis Herrmann, Khue Nguyen, Fabian Theis et al.
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
A foundation model for clinician-centered drug repurposingKexin Huang, Payal Chandak, Qianwen Wang, Shreyas Havaldar, Akhil Vaid et al.
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Large Language Models are Powerful Electronic Health Record EncodersStefan Hegselmann, Georg von Arnim, Tillmann Rheude, Noel Kronenberg, David Sontag et al.
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
JanusDNA: A Powerful Bi-directional Hybrid DNA Foundation ModelQihao Duan, Bingding Huang, Zhenqiao Song, Irina Lehmann, Lei Gu et al.
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health PredictionsEray Erturk, Fahad Kamran, Salar Abbaspourazad, Sean Jewell, Harsh Sharma et al.
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited ModalitiesAdriel Saporta, Aahlad Puli, Mark Goldstein, Rajesh Ranganath
Tillmann Rheude, Leonhard Kohleick, and Benjamin Wild from Berlin Institute of Health at Charité co-hosted this reading group on the variety of machine learning in healthcare, covering medical image segmentation, timeseries learning, multimodal representations, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Lauro Langosco, Jack Koch, Lee Sharkey, Jacob Pfau, Laurent Orseau et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Stephanie Lin, Jacob Hilton, Owain Evans
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Ryan Greenblatt, Carson Denison, Benjamin Wright, Fabien Roger, Monte MacDiarmid et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Jan Betley, Daniel Tan, Niels Warncke, Anna Sztyber-Betley, Xuchan Bao et al.
Craig Dickson hosted this reading group on technical alignment in AI, covering state of the art research on aligning large language models — including RLHF, constitutional AI, adversarial training, goal misgeneralization, and more.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
- Summer Semester 2026
Miles Wang, Tom Dupre la Tour, Olivia Watkins, Aleksandar Makelov, Ryan Andrew Chi et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Jan Betley, Xuchan Bao, Martín Soto, Anna Sztyber-Betley, James Chua et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Bingyi Kang, Yang Yue, Rui Lu, Zhijie Lin, Yang Zhao et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Lorenz Hufe, Constantin Venhoff, Erblina Purelku, Maximilian Dreyer, Sebastian Lapuschkin et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
CancelledReading GroupToken Sparse Attention: Efficient Long-Context Inference with Interleaved Token SelectionDongwon Jo, Beomseok Kang, Jiwon Song, Jae-Joon Kim
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Moonyoung Lee, Uksang Yoo, Jean Oh, Jeffrey Ichnowski, George Kantor et al.
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Claire Chen, Zhongchun Yu, Hojung Choi, Mark Cutkosky, Jeannette Bohg
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
Patrick Lowin, Vito Mengers, Oliver Brock
This summer semester we are hosting a BLISSful AI reading group. Various BLISS members will present papers related to their research.
Location: Merantix AI Campus (Max-Urich-Straße 3, 13355 Berlin)
Time: Every Monday, 6:45pm
More events are being planned — stay tuned!
