Nino Scherrer - RankMe

23 papers A* 3Journal 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Reasoning Models Generate Societies of Thought. CoRR Junsol Kim, Shiyang Lai, Nino Scherrer, Blaise Agüera y Arcas, James Evans
2025	J	`jnl`	Do Depth-Grown Models Overcome the Curse of Depth? An In-Depth Analysis. CoRR Ferdinand Kapl, Emmanouil Angelis, Tobias Höppe, Kaitlin Maile, Johannes von Oswald, Nino Scherrer, Stefan Bauer
2025	J	`jnl`	Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning. CoRR Seijin Kobayashi, Yanick Schimpf, Maximilian Schlegel, Angelika Steger, Maciej Wolczyk, Johannes von Oswald, Nino Scherrer, Kaitlin Maile, Guillaume Lajoie, Blake A. Richards, Rif A. Saurous, James Manyika, Blaise Agüera y Arcas, Alexander Meulemans, João Sacramento
2025	J	`jnl`	MesaNet: Sequence Modeling by Locally Optimal Test-Time Training. CoRR Johannes von Oswald, Nino Scherrer, Seijin Kobayashi, Luca Versari, Songlin Yang, Maximilian Schlegel, Kaitlin Maile, Yanick Schimpf, Oliver Sieberling, Alexander Meulemans, Rif A. Saurous, Guillaume Lajoie, Charlotte Frenkel, Razvan Pascanu, Blaise Agüera y Arcas, João Sacramento
2025	A*	`conf`	Multi-agent cooperation through learning-aware policy gradients. ICLR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2025	J	`jnl`	No for Some, Yes for Others: Persona Prompts and Other Sources of False Refusal in Language Models. CoRR Flor Miriam Plaza del Arco, Paul Röttger, Nino Scherrer, Emanuele Borgonovo, Elmar Plischke, Dirk Hovy
2025	J	`jnl`	Not Every AI Problem Is a Data Problem. Commun. ACM Tanya Rodchenko, Natasha F. Noy, Nino Scherrer
2025	J	`jnl`	Not Every AI Problem is a Data Problem: We Should Be Intentional About Data Scaling. CoRR Tanya Rodchenko, Natasha F. Noy, Nino Scherrer, Jennifer Prendki
2025	J	`jnl`	Review, Refine, Repeat: Understanding Iterative Decoding of AI Agents with Dynamic Evaluation and Selection. CoRR Souradip Chakraborty, Mohammadreza Pourreza, Ruoxi Sun, Yiwen Song, Nino Scherrer, Furong Huang, Amrit Singh Bedi, Ahmad Beirami, Jindong Gu, Hamid Palangi, Tomas Pfister
2025	J	`jnl`	Uncovering Competency Gaps in Large Language Models and Their Benchmarks. CoRR Matyas Bohacek, Nino Scherrer, Nicholas Dufour, Thomas Leung, Christoph Bregler, Stephanie C. Y. Chan
2024	J	`jnl`	Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin N. Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren
2024	J	`jnl`	Multi-agent cooperation through learning-aware policy gradients. CoRR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake A. Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2023	A*	`conf`	Evaluating the Moral Beliefs Encoded in LLMs. NeurIPS Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei
2023	J	`jnl`	Evaluating the Moral Beliefs Encoded in LLMs. CoRR Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei
2023	J	`jnl`	FinanceBench: A New Benchmark for Financial Question Answering. CoRR Pranab Islam, Anand Kannappan, Douwe Kiela, Rebecca Qian, Nino Scherrer, Bertie Vidgen
2023	J	`jnl`	SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models. CoRR Bertie Vidgen, Hannah Rose Kirk, Rebecca Qian, Nino Scherrer, Anand Kannappan, Scott A. Hale, Paul Röttger
2023	A*	`conf`	Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery. NeurIPS Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos
2023	J	`jnl`	Uncovering mesa-optimization algorithms in Transformers. CoRR Johannes von Oswald, Eyvind Niklasson, Maximilian Schlegel, Seijin Kobayashi, Nicolas Zucchet, Nino Scherrer, Nolan Miller, Mark Sandler, Blaise Agüera y Arcas, Max Vladymyrov, Razvan Pascanu, João Sacramento
2022	J	`jnl`	FED-CD: Federated Causal Discovery from Interventional and Observational Data. CoRR Amin Abyaneh, Nino Scherrer, Patrick Schwab, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
2022	J	`jnl`	On the Generalization and Adaption Performance of Causal Models. CoRR Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke
2022	J	`jnl`	Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery. CoRR Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos
2021	J	`jnl`	Learning Neural Causal Models with Active Interventions. CoRR Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke
2021	J	`jnl`	Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer