Julian Martin Eisenschlos

According to our database, Julian Martin Eisenschlos authored at least 27 papers between 2019 and 2024.

Collaborative distances:

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

2024

TableRAG: Million-Token Table Understanding with Language Models.

Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos, Zifeng Wang, Zilong Wang, Yanfei Chen, Yasuhisa Fujii, Hsuan-Tien Lin, Chen-Yu Lee, Tomas Pfister

CoRR, 2024

PaliGemma: A versatile 3B VLM for transfer.

Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai

CoRR, 2024

TANQ: An open domain dataset of table answered questions.

Mubashara Akhtar, Chenxi Pang, Andreea Marzoca, Yasemin Altun, Julian Martin Eisenschlos

CoRR, 2024

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Faithful Chart Summarization with ChaTS-Pi.

Syrine Krichene, Francesco Piccinno, Fangyu Liu, Julian Eisenschlos

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Selectively Answering Visual Questions.

Julian Eisenschlos, Hernán Maina, Guido Ivetta, Luciana Benotti

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding.

Kenton Lee, Mandar Joshi, Iulia Raluca Turc, Hexiang Hu, Fangyu Liu, Julian Martin Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova

Proceedings of the International Conference on Machine Learning, 2023

Universal Self-Adaptive Prompting.

Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Selectively Answering Ambiguous Questions.

Jeremy R. Cole, Michael J. Q. Zhang, Daniel Gillick, Julian Eisenschlos, Bhuwan Dhingra, Jacob Eisenstein

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

WinoDict: Probing language models for in-context word acquisition.

Julian Martin Eisenschlos, Jeremy R. Cole, Fangyu Liu, William W. Cohen

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

DiffQG: Generating Questions to Summarize Factual Changes.

Jeremy R. Cole, Palak Jain, Julian Martin Eisenschlos, Michael J. Q. Zhang, Eunsol Choi, Bhuwan Dhingra

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering.

Fangyu Liu, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Yasemin Altun, Nigel Collier, Julian Martin Eisenschlos

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

DePlot: One-shot visual language reasoning by plot-to-table translation.

Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Wenhu Chen, Nigel Collier, Yasemin Altun

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Time-Aware Language Models as Temporal Knowledge Bases.

Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, Daniel Gillick, Jacob Eisenstein, William W. Cohen

Trans. Assoc. Comput. Linguistics, 2022

Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour.

Fangyu Liu, Julian Martin Eisenschlos, Jeremy R. Cole, Nigel Collier

Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

MiQA: A Benchmark for Inference on Metaphorical Questions.

Iulia M. Comsa, Julian Martin Eisenschlos, Srini Narayanan

Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

Leveraging Data Recasting to Enhance Tabular Reasoning.

Aashna Jena, Vivek Gupta, Manish Shrivastava, Julian Martin Eisenschlos

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Table-To-Text generation and pre-training with TabT5.

Ewa Andrejczuk, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene, Yasemin Altun

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training.

Thomas Müller, Julian Martin Eisenschlos, Syrine Krichene

Proceedings of the 15th International Workshop on Semantic Evaluation, 2021

Open Domain Question Answering over Tables via Dense Retrieval.

Jonathan Herzig, Thomas Müller, Syrine Krichene, Julian Martin Eisenschlos

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

Fool Me Twice: Entailment from Wikipedia Gamification.

Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Börschinger, Jordan L. Boyd-Graber

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

MATE: Multi-view Attention for Table Transformer Efficiency.

Julian Martin Eisenschlos, Maharshi Gor, Thomas Müller, William W. Cohen

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

DoT: An efficient Double Transformer for NLP tasks with tables.

Syrine Krichene, Thomas Müller, Julian Martin Eisenschlos

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

SoftSort: A Continuous Relaxation for the argsort Operator.

Sebastian Prillo, Julian Martin Eisenschlos

Proceedings of the 37th International Conference on Machine Learning, 2020

Understanding tables with intermediate pre-training.

Julian Martin Eisenschlos, Syrine Krichene, Thomas Müller

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

TaPas: Weakly Supervised Table Parsing via Pre-training.

Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, Francesco Piccinno, Julian Martin Eisenschlos

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

MultiFiT: Efficient Multi-lingual Language Model Fine-tuning.

Julian Eisenschlos, Sebastian Ruder, Piotr Czapla, Marcin Kardas, Sylvain Gugger, Jeremy Howard

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019