Torsten Scholak

According to our database, Torsten Scholak authored at least 12 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Apriel-Nemotron-15B-Thinker.

Shruthan Radhakrishna, Soham Parikh, Gopal Sarda, Anil Turkkan, Quaizar Vohra, Raymond Li, Dhruv Jhamb, Kelechi Ogueji, Aanjaneya Shukla, Oluwanifemi Bamgbose, Toby Liang, Luke Kumar, Oleksiy Ostapenko, Shiva Krishna Reddy Malay, Aman Tiwari, Tara Bogavelli, Vikas Yadav, Jash Mehta, Saloni Mittal, Akshay Kalkunte, Pulkit Pattnaik, Khalil Slimi, Anirudh Sreeram, Jishnu Sethumadhavan Nair, Akintunde Oladipo, Shashank Maiya, Khyati Mahajan, Rishabh Maheshwary, Masoud Hashemi, Sai Rajeswar Mudumba, Sathwik Tejaswi Madhusudhan, Torsten Scholak, Sebastien Paquet, Sagar Davasam, Srinivas Sunkara

CoRR, August, 2025

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training.

Oleksiy Ostapenko, Charles Guille-Escuret, Luke Kumar, Max Tian, Denis Kocetkov, Gopeshh Subbaraj, Raymond Li, Joel Lamy-Poirier, Sébastien Paquet, Torsten Scholak

CoRR, July, 2025

Unifying Autoregressive and Diffusion-Based Sequence Generation.

Nima Fathi, Torsten Scholak, Pierre-André Noël

CoRR, April, 2025

2024

TapeAgents: a Holistic Framework for Agent Development and Optimization.

Dzmitry Bahdanau, Nicolas Gontier, Gabriel Huang, Ehsan Kamalloo, Rafael Pardinas, Alexandre Piché, Torsten Scholak, Oleh Shliazhko, Jordan Prince Tremblay, Karam Ghanem, Soham Parikh, Mitul Tiwari, Quaizar Vohra

CoRR, 2024

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks.

Juan A. Rodríguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-André Noël, Mats Leon Richter, Saverio Vadacchino, Shubbam Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Noah Bolger, Kurt MacDonald, Simon Fauvel, Sathwik Tejaswi, Srinivas Sunkara, João Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharagani, Sean Hughes, M. Tamer Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vázquez, Sai Rajeswar

CoRR, 2024

Perplexed: Understanding When Large Language Models are Confused.

Nathan Cooper, Torsten Scholak

CoRR, 2024

StarCoder 2 and The Stack v2: The Next Generation.

Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian J. McAuley, Han Hu, Torsten Scholak, Sébastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, et al.

CoRR, 2024

2023

RepoFusion: Training Code Models to Understand Your Repository.

Disha Shrivastava, Denis Kocetkov, Harm de Vries, Dzmitry Bahdanau, Torsten Scholak

CoRR, 2023

2022

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.

Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Towards Neural Functional Program Evaluation.

Torsten Scholak, Jonathan Pilault, Joey Velez-Ginorio

CoRR, 2021

DuoRAT: Towards Simpler Text-to-SQL Models.

Torsten Scholak, Raymond Li, Dzmitry Bahdanau, Harm de Vries, Chris Pal

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models.

Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021