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Shikhhar Siingh

2 accepted papers

2025

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

ACL 2025long

Publicly significant images from events carry valuable contextual information with applications in domains such as journalism and education. However, existing methodologies often struggle to accurately extract this contextual relevance from images. To address this challenge, we introduce GETREASON (…

Cited by 0SourcePDFScholar
2025

TABARD: A Novel Benchmark for Tabular Anomaly Analysis, Reasoning and Detection

EMNLP 2025

We study the capabilities of large language models (LLMs) in detecting fine-grained anomalies in tabular data. Specifically, we examine: (1) how well LLMs can identify diverse anomaly types including factual, logical, temporal, and value-based errors; (2) the impact of prompt design and prompting st

Cited by 0SourcePDFScholar