MultiFiT: Efficient Multi-lingual Language Model Fine-tuning. - Julian Eisenschlos; Sebastian Ruder; Piotr Czapla; Marcin Kardas; Sylvain Gugger; Jeremy Howard (EMNLP/IJCNLP (1), 2019)

TaPas: Weakly Supervised Table Parsing via Pre-training. - Jonathan Herzig; Pawel Krzysztof Nowak; Thomas Müller 009; Francesco Piccinno; Julian Martin Eisenschlos (ACL, 2020)

Understanding tables with intermediate pre-training. - Julian Martin Eisenschlos; Syrine Krichene; Thomas Müller 009 (EMNLP (Findings), 2020)

SoftSort: A Continuous Relaxation for the argsort Operator. - Sebastian Prillo; Julian Martin Eisenschlos (ICML, 2020)

DoT: An efficient Double Transformer for NLP tasks with tables. - Syrine Krichene; Thomas Müller 009; Julian Martin Eisenschlos (ACL/IJCNLP (Findings), 2021)

MATE: Multi-view Attention for Table Transformer Efficiency. - Julian Martin Eisenschlos; Maharshi Gor; Thomas Müller 009; William W. Cohen (EMNLP (1), 2021)

Fool Me Twice: Entailment from Wikipedia Gamification. - Julian Martin Eisenschlos; Bhuwan Dhingra; Jannis Bulian; Benjamin Börschinger; Jordan L. Boyd-Graber (NAACL-HLT, 2021)

Open Domain Question Answering over Tables via Dense Retrieval. - Jonathan Herzig; Thomas Müller 009; Syrine Krichene; Julian Martin Eisenschlos (NAACL-HLT, 2021)

TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training. - Thomas Müller 009; Julian Martin Eisenschlos; Syrine Krichene (SemEval@ACL/IJCNLP, 2021)

Table-To-Text generation and pre-training with TabT5. - Ewa Andrejczuk; Julian Martin Eisenschlos; Francesco Piccinno; Syrine Krichene; Yasemin Altun (EMNLP (Findings), 2022)

Leveraging Data Recasting to Enhance Tabular Reasoning. - Aashna Jena; Vivek Gupta 001; Manish Shrivastava 001; Julian Martin Eisenschlos (EMNLP (Findings), 2022)

MiQA: A Benchmark for Inference on Metaphorical Questions. - Iulia M. Comsa; Julian Martin Eisenschlos; Srini Narayanan (AACL/IJCNLP (2), 2022)

Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour. - Fangyu Liu 001; Julian Martin Eisenschlos; Jeremy R. Cole; Nigel Collier (AACL/IJCNLP (2), 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)

DePlot: One-shot visual language reasoning by plot-to-table translation. - Fangyu Liu 001; Julian Martin Eisenschlos; Francesco Piccinno; Syrine Krichene; Chenxi Pang; Kenton Lee; Mandar Joshi; Wenhu Chen; Nigel Collier; Yasemin Altun (ACL (Findings), 2023)

MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering. - Fangyu Liu 001; Francesco Piccinno; Syrine Krichene; Chenxi Pang; Kenton Lee; Mandar Joshi; Yasemin Altun; Nigel Collier; Julian Martin Eisenschlos (ACL (1), 2023)

DiffQG: Generating Questions to Summarize Factual Changes. - Jeremy R. Cole; Palak Jain 006; Julian Martin Eisenschlos; Michael J. Q. Zhang; Eunsol Choi; Bhuwan Dhingra (EACL, 2023)

WinoDict: Probing language models for in-context word acquisition. - Julian Martin Eisenschlos; Jeremy R. Cole; Fangyu Liu 001; William W. Cohen (EACL, 2023)

Selectively Answering Ambiguous Questions. - Jeremy R. Cole; Michael J. Q. Zhang; Daniel Gillick; Julian Eisenschlos; Bhuwan Dhingra; Jacob Eisenstein (EMNLP, 2023)

Universal Self-Adaptive Prompting. - Xingchen Wan; Ruoxi Sun 002; Hootan Nakhost; Hanjun Dai; Julian Eisenschlos; Sercan Ö. Arik; Tomas Pfister (EMNLP, 2023)

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding. - Kenton Lee; Mandar Joshi; Iulia Raluca Turc; Hexiang Hu; Fangyu Liu 001; Julian Martin Eisenschlos; Urvashi Khandelwal; Peter Shaw 004; Ming-Wei Chang; Kristina Toutanova (ICML, 2023)

Selectively Answering Visual Questions. - Julian Eisenschlos; Hernán Maina; Guido Ivetta; Luciana Benotti (ACL (Findings), 2024)

Faithful Chart Summarization with ChaTS-Pi. - Syrine Krichene; Francesco Piccinno; Fangyu Liu 001; Julian Eisenschlos (ACL (1), 2024)

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. - Zilong Wang 002; Hao Zhang; Chun-Liang Li; Julian Martin Eisenschlos; Vincent Perot; Zifeng Wang 002; Lesly Miculicich; Yasuhisa Fujii; Jingbo Shang; Chen-Yu Lee; Tomas Pfister (ICLR, 2024)

TableRAG: Million-Token Table Understanding with Language Models. - Si-An Chen; Lesly Miculicich; Julian Eisenschlos; Zifeng Wang 002; Zilong Wang 002; Yanfei Chen; Yasuhisa Fujii; Hsuan-Tien Lin; Chen-Yu Lee; Tomas Pfister (NeurIPS, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts. - Negar Foroutan; Angelika Romanou; Matin Ansaripour; Julian Martin Eisenschlos; Karl Aberer; Rémi Lebret (ACL (Findings), 2025)

TANQ: An Open Domain Dataset of Table Answered Questions. - Mubashara Akhtar; Chenxi Pang; Andreea Marzoca; Yasemin Altun; Julian Martin Eisenschlos (Trans. Assoc. Comput. Linguistics, 2025)

ROSA: Addressing text understanding challenges in photographs via ROtated SAmpling. - Hernán Maina; Guido Ivetta; Mateo Lione Stuto; Julian Martin Eisenschlos; Jorge Sánchez; Luciana Benotti (CoRR, 2025)