most citedInterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information

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cs.CL20261 cited

InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information

Anirudh Iyengar Kaniyar Narayana Iyengar, Srija Mukhopadhyay, Adnan Qidwai +3

We introduce InterChart, a diagnostic benchmark that evaluates how well vision-language models (VLMs) reason across multiple related charts, a task central to real-world applicatio…

cs.CL2026

CRAFT: Training-Free Cascaded Retrieval for Tabular QA

Adarsh Singh, Kushal Raj Bhandari, Jianxi Gao +2

Open-Domain Table Question Answering (TQA) involves retrieving relevant tables from a large corpus to answer natural language queries. Traditional dense retrieval models such as DT…

cs.CL2026

QUIETT: Query-Independent Table Transformation for Robust Reasoning

Gaurav Najpande, Tampu Ravi Kumar, Manan Roy Choudhury +3

Real-world tables often contain schema inconsistencies, heterogeneous value formats, and implicit relational structures that degrade table reasoning and question answering. Existin…

cs.CL2026

ViTaB-A: Evaluating Multimodal Large Language Models on Visual Table Attribution

Yahia Alqurnawi, Preetom Biswas, Anmol Rao +3

Multimodal Large Language Models (mLLMs) are often used to answer questions in structured data such as tables in Markdown, JSON, and images. While these models can often give corre…

cs.CL2026

TraceBack: Multi-Agent Decomposition for Fine-Grained Table Attribution

Tejas Anvekar, Junha Park, Rajat Jha +4

Question answering (QA) over structured tables requires not only accurate answers but also transparency about which cells support them. Existing table QA systems rarely provide fin…

cs.CL2025

Evidence-Guided Schema Normalization for Temporal Tabular Reasoning

Ashish Thanga, Vibhu Dixit, Abhilash Shankarampeta +1

Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose a SQL-based approach that involves (1) generating a 3NF schema from Wiki…