IMAgent trains a multi-image vision agent via pure end-to-end RL with visual reflection tools and a two-layer motion trajectory masking strategy, reaching SOTA on single- and multi-image benchmarks while revealing tool-use effects on attention.
PosterSum: A multimodal benchmark for scientific poster summarization.arXiv preprint arXiv:2502.17540, 2025
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Any2Poster Bench tests poster generation from 8 modalities and 5 domains using quizzes and VLM judgments; Any2Poster Agent reaches 87% accuracy and beats prior paper-only methods.
SciPostGen supplies a paired dataset linking paper structure to poster layouts and shows that retrieval of matching layouts improves generation while respecting user constraints.
VideoAgent is a modular framework that redefines scientific video synthesis as an intent-driven planning problem and introduces the SciVidEval benchmark for multimodal quality and pedagogical utility.
PosterForest uses a hierarchical Poster Tree and content-layout agent collaboration to generate scientific posters from papers without training, outperforming prior automated methods in human and automated evaluation.
citing papers explorer
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Training Multi-Image Vision Agents via End2End Reinforcement Learning
IMAgent trains a multi-image vision agent via pure end-to-end RL with visual reflection tools and a two-layer motion trajectory masking strategy, reaching SOTA on single- and multi-image benchmarks while revealing tool-use effects on attention.
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Any2Poster: Any-Source Poster Generation Across Modalities and Domains
Any2Poster Bench tests poster generation from 8 modalities and 5 domains using quizzes and VLM judgments; Any2Poster Agent reaches 87% accuracy and beats prior paper-only methods.
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SciPostGen: Bridging the Gap between Scientific Papers and Poster Layouts
SciPostGen supplies a paired dataset linking paper structure to poster layouts and shows that retrieval of matching layouts improves generation while respecting user constraints.
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VideoAgent: Personalized Synthesis of Scientific Videos
VideoAgent is a modular framework that redefines scientific video synthesis as an intent-driven planning problem and introduces the SciVidEval benchmark for multimodal quality and pedagogical utility.
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PosterForest: Hierarchical Multi-Agent Collaboration for Scientific Poster Generation
PosterForest uses a hierarchical Poster Tree and content-layout agent collaboration to generate scientific posters from papers without training, outperforming prior automated methods in human and automated evaluation.