1 citations · 1 across the 9 of their papers we have counts for
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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…
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…
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 an approach that recasts the task as automated knowledge base constructi…
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…
MapIQ: Evaluating Multimodal Large Language Models for Map Question Answering
Varun Srivastava, Fan Lei, Srija Mukhopadhyay +2
Recent advancements in multimodal large language models (MLLMs) have driven researchers to explore how well these models read data visualizations, e.g., bar charts, scatter plots.…
Follow the Flow: Fine-grained Flowchart Attribution with Neurosymbolic Agents
Manan Suri, Puneet Mathur, Nedim Lipka +4
Flowcharts are a critical tool for visualizing decision-making processes. However, their non-linear structure and complex visual-textual relationships make it challenging to interp…
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…