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20242026
most citedShould We Fine-Tune or RAG? Evaluating Different Techniques to Adapt LLMs for Dialogue

4 citations · 4 across the 8 of their papers we have counts for

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cs.AI2026

V-DyKnow: A Dynamic Benchmark for Time-Sensitive Knowledge in Vision Language Models

Seyed Mahed Mousavi, Christian Moiola, Massimo Rizzoli +2

Vision-Language Models (VLMs) are trained on data snapshots of documents, including images and texts. Their training data and evaluation benchmarks are typically static, implicitly…

cs.CV2026

Getting to the Point: Pointing Improves LVLMs at Counting

Simone Alghisi, Massimo Rizzoli, Seyed Mahed Mousavi +1

Pointing-based methods decompose complex tasks as sequential grounding and reasoning steps. Given a query, the model first grounds the relevant objects by generating their coordina…