✨PIRA-Bench: A Transition from Reactive GUI Agents to GUI-based Proactive Intent Recommendation Agents

📝 Summary:
PIRA-Bench presents a benchmark for evaluating multimodal large language models on proactive GUI agent tasks using continuous visual inputs, while PIRF offers a memory-aware framework for handling com...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08013
• PDF: https://arxiv.org/pdf/2603.08013
• Project Page: https://www.pira-bench.top

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✨PureCC: Pure Learning for Text-to-Image Concept Customization

📝 Summary:
PureCC presents a concept customization method that preserves original model behavior through decoupled learning and adaptive guidance scaling. AI-generated summary Existing concept customization meth...

🔹 Publication Date: Published on Mar 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07561
• PDF: https://arxiv.org/pdf/2603.07561
• Github: https://github.com/lzc-sg/PureCC

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✨From Narrow to Panoramic Vision: Attention-Guided Cold-Start Reshapes Multimodal Reasoning

📝 Summary:
The study introduces a novel attention-based metric called Visual Attention Score to analyze cold-start initialization in multimodal large reasoning models, identifying a counter-intuitive phenomenon ...

🔹 Publication Date: Published on Mar 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.03825
• PDF: https://arxiv.org/pdf/2603.03825
• Github: https://github.com/lrlbbzl/Qwen-AVAR

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✨Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence

📝 Summary:
Holi-Spatial presents the first fully automated, large-scale, spatially-aware multimodal dataset constructed from raw video inputs, supporting multi-level spatial supervision for 3D scene understandin...

🔹 Publication Date: Published on Mar 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07660
• PDF: https://arxiv.org/pdf/2603.07660
• Project Page: https://visionary-laboratory.github.io/holi-spatial/
• Github: https://github.com/Visionary-Laboratory/holi-spatial

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✨\$OneMillion-Bench: How Far are Language Agents from Human Experts?

📝 Summary:
A new benchmark evaluates language models on complex, real-world professional tasks requiring multi-step reasoning, evidence resolution, and domain-specific decision-making across multiple industries....

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07980
• PDF: https://arxiv.org/pdf/2603.07980
• Github: https://github.com/humanlaya/OneMillion-Bench

==================================

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✨Believe Your Model: Distribution-Guided Confidence Calibration

📝 Summary:
Large reasoning models enhance prediction accuracy through test-time scaling techniques that generate multiple candidate responses, with the proposed DistriVoting method utilizing distributional prior...

🔹 Publication Date: Published on Mar 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.03872
• PDF: https://arxiv.org/pdf/2603.03872
• Github: https://github.com/yxizhong/SSC

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✨Scale Space Diffusion

📝 Summary:
Scale-space theory connects diffusion models' information hierarchy to low-pass filtering, leading to a framework that combines scale spaces with diffusion processes for efficient image processing. AI...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08709
• PDF: https://arxiv.org/pdf/2603.08709
• Project Page: https://prateksha.github.io/projects/scale-space-diffusion/
• Github: https://github.com/prateksha/ScaleSpaceDiffusion

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✨FVG-PT: Adaptive Foreground View-Guided Prompt Tuning for Vision-Language Models

📝 Summary:
Foreground attention shifts during CLIP-based prompt tuning are addressed through an adaptive module that enhances foreground view quality and mitigates generalization degradation. AI-generated summar...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08708
• PDF: https://arxiv.org/pdf/2603.08708
• Github: https://github.com/JREion/FVG-PT

✨ Datasets citing this paper:
• https://huggingface.co/datasets/JREion/Prompt_Tuning_Datasets_with_Foreground

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✨Skip to the Good Part: Representation Structure & Inference-Time Layer Skipping in Diffusion vs. Autoregressive LLMs

📝 Summary:
Diffusion language models exhibit distinct representational structures compared to autoregressive models, with hierarchical abstractions and reduced bias, enabling efficient layer-skipping inference w...

🔹 Publication Date: Published on Mar 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07475
• PDF: https://arxiv.org/pdf/2603.07475

==================================

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✨Scaling Agentic Capabilities, Not Context: Efficient Reinforcement Finetuning for Large Toolspaces

📝 Summary:
ATLAS enables small language models to effectively operate in large-scale tool environments through reinforcement fine-tuning that learns context control and execution structure, achieving performance...

🔹 Publication Date: Published on Mar 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.06713
• PDF: https://arxiv.org/pdf/2603.06713

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✨Agentic Critical Training

📝 Summary:
Agentic Critical Training (ACT) is a reinforcement learning approach that trains language model agents to autonomously reason about action quality by directly rewarding correct judgment between altern...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08706
• PDF: https://arxiv.org/pdf/2603.08706
• Project Page: https://attention-is-all-i-need.github.io/ACT/

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✨OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning

📝 Summary:
OfficeQA Pro evaluates AI agents on multi-document reasoning across historical financial documents, revealing persistent challenges in grounded reasoning despite advanced model capabilities. AI-genera...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08655
• PDF: https://arxiv.org/pdf/2603.08655
• Github: https://github.com/databricks/officeqa

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✨HiAR: Efficient Autoregressive Long Video Generation via Hierarchical Denoising

📝 Summary:
HiAR, a hierarchical autoregressive diffusion framework, improves video generation by conditioning on context at the same noise level and employs forward-KL regularization to maintain temporal continu...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08703
• PDF: https://arxiv.org/pdf/2603.08703
• Project Page: https://jacky-hate.github.io/HiAR/
• Github: https://jacky-hate.github.io/HiAR/

🔹 Models citing this paper:
• https://huggingface.co/jackyhate/HiAR

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✨NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving

📝 Summary:
NaviDriveVLM presents a decoupled vision-language model framework for autonomous driving that separates high-level reasoning from motion planning, achieving superior performance in end-to-end driving ...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07901
• PDF: https://arxiv.org/pdf/2603.07901
• Github: https://github.com/TAMU-CVRL/NaviDrive

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✨CARE-Edit: Condition-Aware Routing of Experts for Contextual Image Editing

📝 Summary:
CARE-Edit introduces a condition-aware routing mechanism that dynamically allocates diffusion model computation to specialized experts for improved contextual image editing tasks. AI-generated summary...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08589
• PDF: https://arxiv.org/pdf/2603.08589
• Project Page: https://care-edit.github.io/
• Github: https://care-edit.github.io/

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✨Spatiotemporal Heterogeneity of AI-Driven Traffic Flow Patterns and Land Use Interaction: A GeoAI-Based Analysis of Multimodal Urban Mobility

📝 Summary:
A GeoAI Hybrid framework combining MGWR, RF, and ST-GCN models effectively captures complex traffic flow patterns and land use interactions across multiple mobility modes with superior predictive perf...

🔹 Publication Date: Published on Mar 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.05581
• PDF: https://arxiv.org/pdf/2603.05581

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✨AutoResearch-RL: Perpetual Self-Evaluating Reinforcement Learning Agents for Autonomous Neural Architecture Discovery

📝 Summary:
An autonomous reinforcement learning framework conducts continuous neural architecture and hyperparameter research without human intervention, achieving performance comparable to hand-tuned baselines ...

🔹 Publication Date: Published on Mar 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07300
• PDF: https://arxiv.org/pdf/2603.07300

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✨Autophoresis of a Janus particle near a planar wall: a lubrication limit

📝 Summary:
We study the self-diffusiophoresis of a spherical chemically active particle near a planar, impermeable wall, with a focus on the influence of particle orientation on propulsion. We analyze a Janus pa...

🔹 Publication Date: Published on Feb 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00791
• PDF: https://arxiv.org/pdf/2603.00791

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✨LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory

📝 Summary:
LoGeR enables long-term 3D video reconstruction by combining bidirectional priors with a hybrid memory system that includes parametric Test-Time Training and non-parametric sliding window attention me...

🔹 Publication Date: Published on Mar 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.03269
• PDF: https://arxiv.org/pdf/2603.03269
• Project Page: https://loger-project.github.io/
• Github: https://github.com/Junyi42/LoGeR

🔹 Models citing this paper:
• https://huggingface.co/Junyi42/LoGeR

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✨How Far Can Unsupervised RLVR Scale LLM Training?

📝 Summary:
Intrinsic Unsupervised RL with Verifiable Rewards URLVR for LLMs faces fundamental scaling limits. It fails due to confidence-correction misalignment, leading to collapse. External reward methods show promise for overcoming these barriers.

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08660
• PDF: https://arxiv.org/pdf/2603.08660
• Github: https://github.com/PRIME-RL/TTRL/tree/urlvr-dev

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