✨UnicEdit-10M: A Dataset and Benchmark Breaking the Scale-Quality Barrier via Unified Verification for Reasoning-Enriched Edits

📝 Summary:
This paper tackles image editing model performance gaps due to data scarcity by introducing UnicEdit-10M, a 10M-scale high-quality dataset from a lightweight verified pipeline. It also proposes UnicBench, a new benchmark with novel metrics to diagnose reasoning limitations in models.

🔹 Publication Date: Published on Dec 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02790
• PDF: https://arxiv.org/pdf/2512.02790

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#ImageEditing #AI #Dataset #Benchmark #ComputerVision

✨OmniSafeBench-MM: A Unified Benchmark and Toolbox for Multimodal Jailbreak Attack-Defense Evaluation

📝 Summary:
OmniSafeBench-MM is a unified toolbox for evaluating multi-modal jailbreak attacks and defenses in MLLMs. It integrates various attacks, defense strategies, and a diverse dataset to provide a comprehensive, standardized, and reproducible platform for research.

🔹 Publication Date: Published on Dec 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06589
• PDF: https://arxiv.org/pdf/2512.06589

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#MLLMs #AISafety #AIsecurity #Benchmark #DeepLearning

✨AgentIF-OneDay: A Task-level Instruction-Following Benchmark for General AI Agents in Daily Scenarios

📝 Summary:
AgentIF-OneDay is a new benchmark evaluating AI agents on diverse daily tasks using natural language instructions. It assesses problem-solving, attachment understanding, and file-based outputs across three user-centric categories. Benchmarking shows leading agent products and LLM APIs excel in th...

🔹 Publication Date: Published on Jan 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.20613
• PDF: https://arxiv.org/pdf/2601.20613

✨ Datasets citing this paper:
• https://huggingface.co/datasets/xbench/AgentIF-OneDay

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#AIAgents #LLMs #Benchmark #InstructionFollowing #GeneralAI

✨LangMap: A Hierarchical Benchmark for Open-Vocabulary Goal Navigation

📝 Summary:
HieraNav introduces a multi-granularity, open-vocabulary navigation task. LangMap, its benchmark, uses 3D scans and human annotations across four semantic levels. Evaluations highlight challenges for models in complex navigation goals.

🔹 Publication Date: Published on Feb 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02220
• PDF: https://arxiv.org/pdf/2602.02220
• Project Page: https://bo-miao.github.io/LangMap/
• Github: https://github.com/bo-miao/LangMap

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#AINavigation #ComputerVision #Robotics #NLP #Benchmark

✨EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies

📝 Summary:
EcoGym introduces a new benchmark for evaluating LLM agents long-horizon planning in interactive economic environments. It features three diverse scenarios with persistent dynamics and business-relevant metrics. Experiments reveal LLMs struggle with either high-level strategy or efficient action ...

🔹 Publication Date: Published on Feb 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09514
• PDF: https://arxiv.org/pdf/2602.09514
• Github: https://github.com/OPPO-PersonalAI/EcoGym

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#LLM #AIPlanning #EconomicSimulation #AI #Benchmark

✨RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies

📝 Summary:
RoboMME introduces a large-scale standardized benchmark for evaluating memory in vision-language-action models for long-horizon robotic manipulation. It comprises 16 tasks assessing temporal, spatial, object, and procedural memory. Experiments show memory effectiveness is highly task-dependent, w...

🔹 Publication Date: Published on Mar 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.04639
• PDF: https://arxiv.org/pdf/2603.04639
• Project Page: https://robomme.github.io/
• Github: https://github.com/RoboMME/robomme_benchmark

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#Robotics #AI #Benchmark #RoboticManipulation #Memory

✨According to Me: Long-Term Personalized Referential Memory QA

📝 Summary:
ATM-Bench is a new benchmark for multimodal multi-source personalized referential memory QA, addressing limitations of existing dialogue-focused benchmarks. It includes 4 years of personal data and introduces Schema-Guided Memory SGM. Current AI systems perform poorly under 20 percent on hard set...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01990
• PDF: https://arxiv.org/pdf/2603.01990
• Project Page: https://atmbench.github.io/
• Github: https://github.com/JingbiaoMei/ATM-Bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Jingbiao/ATM-Bench

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#AI #QuestionAnswering #LongTermMemory #MachineLearning #Benchmark

✨HomeSafe-Bench: Evaluating Vision-Language Models on Unsafe Action Detection for Embodied Agents in Household Scenarios

📝 Summary:
HomeSafe-Bench presents a benchmark for vision-language models to detect unsafe actions by embodied agents in household settings. It also introduces HD-Guard, a hierarchical dual-brain architecture balancing real-time safety monitoring with detection accuracy.

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11975
• PDF: https://arxiv.org/pdf/2603.11975
• Project Page: https://pujiayue.github.io/homesafe-bench.github.io/
• Github: https://github.com/pujiayue/HomeSafe-Bench

✨ Spaces citing this paper:
• https://huggingface.co/spaces/pujiayue/HomeSafe-Bench-Leaderboard

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#VisionLanguageModels #EmbodiedAI #AISafety #Robotics #Benchmark

✨RealChart2Code: Advancing Chart-to-Code Generation with Real Data and Multi-Task Evaluation

📝 Summary:
RealChart2Code is a new benchmark assessing VLM ability to generate complex, multi-panel charts from real data. It reveals significant performance gaps between proprietary and open-weight models, highlighting VLM struggles with intricate plots.

🔹 Publication Date: Published on Mar 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.25804
• PDF: https://arxiv.org/pdf/2603.25804
• Project Page: https://huggingface.co/datasets/zjj1233/RealChart2Code
• Github: https://github.com/Speakn0w/RealChart2Code

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#VLM #ChartToCode #Benchmark #AI #DataScience

✨SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing

📝 Summary:
This paper presents SpatialEdit-Bench, a new benchmark and dataset for fine-grained image spatial editing. It introduces SpatialEdit-16B, a model that substantially outperforms prior methods on spatial manipulation, offering precise control over object layout and camera viewpoints.

🔹 Publication Date: Published on Apr 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.04911
• PDF: https://arxiv.org/pdf/2604.04911
• Project Page: https://github.com/EasonXiao-888/SpatialEdit
• Github: https://github.com/EasonXiao-888/SpatialEdit

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#ImageEditing #ComputerVision #DeepLearning #AI #Benchmark