collaborators

9 papers

cs.IR2026

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models

Yuanyuan Tian, Wenwen Li, Xiao Chen +4

Semantic search and recommendation of similar documents, such as news and reports about unusual environmental events (e.g., a dead whale washed ashore in Alaska) that contain spati…

cs.CV2026

MMTABREAL: Real-World Benchmark for Multimodal Table Understanding

Prasham Titiya, Jainil Trivedi, Chitta Baral +1

Multimodal tables i.e. tabular layouts interleaved with charts, maps, icons, and color encodings are ubiquitous in real applications yet remain difficult for Multimodal Large Langu…

cs.CL2026

Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective

Krishna Singh Rajput, Tejas Anvekar, Chitta Baral +1

Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large language models. While these approache…

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.CV2025

The Perceptual Observatory Characterizing Robustness and Grounding in MLLMs

Tejas Anvekar, Fenil Bardoliya, Pavan K. Turaga +2

Recent advances in multimodal large language models (MLLMs) have yielded increasingly powerful models, yet their perceptual capacities remain poorly characterized. In practice, mos…

cs.CV2025

GETReason: Enhancing Image Context Extraction through Hierarchical Multi-Agent Reasoning

Shikhhar Siingh, Abhinav Rawat, Chitta Baral +1

Publicly significant images from events hold valuable contextual information, crucial for journalism and education. However, existing methods often struggle to extract this relevan…