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Aashish Anantha Ramakrishnan

3 accepted papers

2025

CORDIAL: Can Multimodal Large Language Models Effectively Understand Coherence Relationships?

ACL 2025long

Multimodal Large Language Models (MLLMs) are renowned for their superior instruction-following and reasoning capabilities across diverse problem domains. However, existing benchmarks primarily focus on assessing factual and logical correctness in downstream tasks, with limited emphasis on evaluating…

2025

From Intentions to Techniques: A Comprehensive Taxonomy and Challenges in Text Watermarking for Large Language Models

NAACL 2025findings

With the rapid growth of Large Language Models (LLMs), safeguarding textual content against unauthorized use is crucial. Watermarking offers a vital solution, protecting both - LLM-generated and plain text sources. This paper presents a unified overview of different perspectives behind designing wat…

Cited by 2SourcePDFScholar
2025

LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles

EMNLP 2025

Figure captions are crucial for helping readers understand and remember a figure’s key message. Many models have been developed to generate these captions, helping authors compose better quality captions more easily. Yet, authors almost always need to revise generic AI-generated captions to match th