Papers by Nicholas Moratelli

2 papers
Benchmarking Deflection and Hallucination in Large Vision-Language Models (2026.acl-long)

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Challenge: Existing benchmarks overlook conflicts between visual and textual evidence and the importance of generating deflections when incomplete knowledge is retrieved.
Approach: They propose a dynamic curation pipeline that preserves benchmark difficulty over time . they propose 'vlm-DeflectionBench' benchmark to probe model behaviour under conflicting evidence .
Outcome: The proposed benchmarks overlook conflicts between visual and textual evidence and are prone to obsolescence . the proposed benchmark is based on 2,775 samples spanning diverse retrieval settings .
The Revolution of Multimodal Large Language Models: A Survey (2024.findings-acl)

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Challenge: Recent advances in large language models have led to the development of multimodal large language model.
Approach: They present a review of recent visual-based Large Language Models and analyze their architectures and alignment strategies.
Outcome: The proposed models can integrate visual and textual modalities while providing a dialogue-based interface and instruction-following capabilities.

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