10 papers
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…
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…
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…
SAGE: Structure Aware Graph Expansion for Retrieval of Heterogeneous Data
Prasham Titiya, Rohit Khoja, Tomer Wolfson +2
Retrieval-augmented question answering over heterogeneous corpora requires connected evidence across text, tables, and graph nodes. While entity-level knowledge graphs support stru…
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…
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…