most citedPragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges

1 citations · 1 across the 6 of their papers we have counts for

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6 papers

cs.CL2025

Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation

Wei Zhou, Bolei Ma, Annemarie Friedrich +1

Table Question Answering (TQA) aims to answer natural language questions about tabular data, often accompanied by additional contexts such as text passages. The task spans diverse…

cs.CL2025

Texts or Images? A Fine-grained Analysis on the Effectiveness of Input Representations and Models for Table Question Answering

Wei Zhou, Mohsen Mesgar, Heike Adel +1

In table question answering (TQA), tables are encoded as either texts or images. Prior work suggests that passing images of tables to multi-modal large language models (MLLMs) perf…

cs.CL2025

p2-TQA: A Process-based Preference Learning Framework for Self-Improving Table Question Answering Models

Wei Zhou, Mohsen Mesgar, Heike Adel +1

Table question answering (TQA) focuses on answering questions based on tabular data. Developing TQA systems targets effective interaction with tabular data for tasks such as cell r…

cs.CL2025★ 1 cited

Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges

Bolei Ma, Yuting Li, Wei Zhou +7

Understanding pragmatics-the use of language in context-is crucial for developing NLP systems capable of interpreting nuanced language use. Despite recent advances in language tech…

cs.CL2024

Efficient Multi-Agent Collaboration with Tool Use for Online Planning in Complex Table Question Answering

Wei Zhou, Mohsen Mesgar, Annemarie Friedrich +1

Complex table question answering (TQA) aims to answer questions that require complex reasoning, such as multi-step or multi-category reasoning, over data represented in tabular for…

cs.CL2024

FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering

Wei Zhou, Mohsen Mesgar, Heike Adel +1

Table Question Answering (TQA) aims at composing an answer to a question based on tabular data. While prior research has shown that TQA models lack robustness, understanding the un…