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20212026
most citedDataComp: In search of the next generation of multimodal datasets

74 citations · 209 across the 38 of their papers we have counts for

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7 papers · 1 filter

cs.CL2025

The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality

Aileen Cheng, Alon Jacovi, Amir Globerson +62

We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually…

cs.CV2025

Error-Driven Scene Editing for 3D Grounding in Large Language Models

Yue Zhang, Zun Wang, Han Lin +5

Despite recent progress in 3D-LLMs, they remain limited in accurately grounding language to visual and spatial elements in 3D environments. This limitation stems in part from train…

cs.CV2025

EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits

Ron Yosef, Moran Yanuka, Yonatan Bitton +1

Text-guided image editing, fueled by recent advancements in generative AI, is becoming increasingly widespread. This trend highlights the need for a comprehensive framework to veri…

cs.CL2025

Unblocking Fine-Grained Evaluation of Detailed Captions: An Explaining AutoRater and Critic-and-Revise Pipeline

Brian Gordon, Yonatan Bitton, Andreea Marzoca +4

Large Vision-Language Models (VLMs) now generate highly detailed, paragraphlength image captions, yet evaluating their factual accuracy remains challenging. Current methods often m…

cs.CV2025

RefVNLI: Towards Scalable Evaluation of Subject-driven Text-to-image Generation

Aviv Slobodkin, Hagai Taitelbaum, Yonatan Bitton +7

Subject-driven text-to-image (T2I) generation aims to produce images that align with a given textual description, while preserving the visual identity from a referenced subject ima…

cs.CV2025

3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model

Wenbo Hu, Yining Hong, Yanjun Wang +7

Humans excel at performing complex tasks by leveraging long-term memory across temporal and spatial experiences. In contrast, current Large Language Models (LLMs) struggle to effec…

cs.CV2025

VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

Hritik Bansal, Clark Peng, Yonatan Bitton +3

Large-scale video generative models, capable of creating realistic videos of diverse visual concepts, are strong candidates for general-purpose physical world simulators. However,…