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Large Language Models (LLMs), already shown to ace various unstructured text comprehension tasks, have also remarkably been shown to tackle table (structured) comprehension tasks without specific training.
Compositional Semantic Parsing on Semi-Structured Tables
Panupong Pasupat and Percy Liang · 2015
Earlier work this paper cites.
What Does BERT Look at? An Analysis of BERT’s Attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning · 2019
Earlier work this paper cites.
TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance
Fengbin Zhu, Wenqiang Lei, Youcheng Huang, Chao Wang, Shuo Zhang, Jiancheng Lv, Fuli Feng, and Tat-Seng Chua · 2021
Earlier work this paper cites.
Robust (Controlled) Table-to-Text Generation with Structure-Aware Equivariance Learning
Fei Wang, Zhewei Xu, Pedro Szekely, and Muhao Chen · 2022
Earlier work this paper cites.
Emergent Abilities of Large Language Models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus · 2022
Earlier work this paper cites.
TableFormer: Robust transformer modeling for table-text encoding
Jingfeng Yang, Aditya Gupta, Shyam Upadhyay, Luheng He, Rahul Goel, and Shachi Paul · 2022
Earlier work this paper cites.
Language models are realistic tabular data generators
Vadim Borisov, Kathrin Sessler, Tobias Leemann, Martin Pawelczyk, and Gjergji Kasneci · 2023
Earlier work this paper cites.
Rethinking Tabular Data Understanding with Large Language Models, 2023
Tianyang Liu, Fei Wang, and Muhao Chen · 2023
Cited alongside, same era.
SCITAB: A Challenging Benchmark for Compositional Reasoning and Claim Verification on Scientific Tables
Xinyuan Lu, Liangming Pan, Qian Liu, Preslav Nakov, and Min-Yen Kan · 2023
Cited alongside, same era.
Stabilizing transformer training by preventing attention entropy collapse
Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, and Josh Susskind · 2023
Cited alongside, same era.
RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbations
Yilun Zhao, Chen Zhao, Linyong Nan, Zhenting Qi, Wenlin Zhang, Xiangru Tang, Boyu Mi, and Dragomir Radev · 2023
Cited alongside, same era.
Entropy– and distance-regularized attention improves low-resource neural machine translation
Ali Araabi, Vlad Niculae, and Christof Monz · 2024
Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion?
Yusuke Sakai, Hidetaka Kamigaito, Katsuhiko Hayashi, and Taro Watanabe · 2024
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Layer by Layer: Uncovering Where Multi-Task Learning Happens in Instruction-Tuned Large Language Models
Zheng Zhao, Yftah Ziser, and Shay B Cohen · 2024
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FREB-TQA: A fine-grained robustness evaluation benchmark for table question answering
Wei Zhou, Mohsen Mesgar, Heike Adel, and Annemarie Friedrich · 2024
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Why do LLMs attend to the first token?, April 2025
Federico Barbero, Álvaro Arroyo, Xiangming Gu, Christos Perivolaropoulos, Michael Bronstein, Petar Veličkovi ć, and Razvan Pascanu · 2025
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Nolima: Long-context evaluation beyond literal matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt, Trung Bui, Ryan A. Rossi, Seunghyun Yoon, and Hinrich Schuetze · 2025
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Cited alongside, same era.
Xi Fang, Weijie Xu, Fiona Anting Tan, Jiani Zhang, Ziqing Hu, Yanjun Qi, Scott Nickleach, Diego Socolinsky, Srinivasan Sengamedu, and Christos Faloutsos · 2024
Cited alongside, same era.
Attention entropy is a key factor: An analysis of parallel context encoding with full-attention-based pre-trained language models
Zhisong Zhang, Yan Wang, Xinting Huang, Tianqing Fang, Hongming Zhang, Chenlong Deng, Shuaiyi Li, and Dong Yu · 2025
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