✨VGGT-Det: Mining VGGT Internal Priors for Sensor-Geometry-Free Multi-View Indoor 3D Object Detection

📝 Summary:
VGGT-Det enables sensor-geometry-free multi-view indoor 3D object detection. It integrates a Visual Geometry Grounded Transformer, using Attention-Guided Query Generation and Query-Driven Feature Aggregation to leverage VGGT's internal semantic and geometric priors. This approach significantly ou...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00912
• PDF: https://arxiv.org/pdf/2603.00912
• Github: https://github.com/yangcaoai/VGGT-Det-CVPR2026

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✨LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model

📝 Summary:
LLaDA-o is an omni diffusion model that uses a Mixture of Diffusion framework to jointly handle text understanding and visual generation through a shared attention backbone, achieving state-of-the-art...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01068
• PDF: https://arxiv.org/pdf/2603.01068
• Github: https://github.com/ML-GSAI/LLaDA-o

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✨Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data

📝 Summary:
Tool-R0 framework enables training general-purpose tool-calling agents through self-play reinforcement learning without initial datasets, achieving significant performance improvements over base model...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://huggingface.co/collections/emrecanacikgoz/tool-r0
• PDF: https://arxiv.org/pdf/2602.21320
• Project Page: https://emrecanacikgoz.github.io/Tool-R0/
• Github: https://github.com/emrecanacikgoz/Tool-R0

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✨Half-Truths Break Similarity-Based Retrieval

📝 Summary:
CLIP-style models exhibit vulnerabilities to half-truths where incorrect details can increase similarity scores, which is addressed through component-supervised fine-tuning that improves compositional...

🔹 Publication Date: Published on Feb 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23906
• PDF: https://arxiv.org/pdf/2602.23906
• Github: https://github.com/kargibora/CS-CLIP

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✨Legal RAG Bench: an end-to-end benchmark for legal RAG

📝 Summary:
Legal RAG Bench evaluates legal retrieval-augmented generation systems using a comprehensive dataset and factorial analysis, revealing that information retrieval significantly impacts performance more...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01710
• PDF: https://arxiv.org/pdf/2603.01710
• Project Page: https://isaacus.com/blog/legal-rag-bench
• Github: https://github.com/isaacus-dev/legal-rag-bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/isaacus/legal-rag-bench

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✨RubricBench: Aligning Model-Generated Rubrics with Human Standards

📝 Summary:
RubricBench is introduced as a benchmark for evaluating rubric-guided reward models in large language model alignment, addressing the lack of discriminative complexity and ground-truth annotations in ...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01562
• PDF: https://arxiv.org/pdf/2603.01562
• Project Page: https://huggingface.co/datasets/DonJoey/rubricbench
• Github: https://github.com/planepig/rubricbench

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✨OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens

📝 Summary:
OmniLottie framework generates high-quality vector animations from multi-modal instructions using a specialized Lottie tokenizer and pretrained vision-language models. AI-generated summary Omni Lottie...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02138
• PDF: https://arxiv.org/pdf/2603.02138
• Project Page: https://openvglab.github.io/OmniLottie/
• Github: https://github.com/OpenVGLab/OmniLottie

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✨LaSER: Internalizing Explicit Reasoning into Latent Space for Dense Retrieval

📝 Summary:
LaSER introduces a self-distillation framework that embeds explicit reasoning into dense retrievers' latent space through dual-view training and multi-grained alignment, enabling efficient reasoning w...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01425
• PDF: https://arxiv.org/pdf/2603.01425

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✨When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains

📝 Summary:
Reinforcement learning enhances medical vision-language model performance primarily by sharpening output distributions when models already have sufficient reasoning support, with supervised fine-tunin...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01301
• PDF: https://arxiv.org/pdf/2603.01301
• Project Page: https://medbridgerl.github.io/
• Github: https://github.com/armenjeddi/medbridgerl

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✨RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment

📝 Summary:
RAISE is a training-free, requirement-driven evolutionary framework that adaptively improves text-to-image generation by dynamically allocating computational resources based on prompt complexity throu...

🔹 Publication Date: Published on Feb 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00483
• PDF: https://arxiv.org/pdf/2603.00483
• Github: https://github.com/LiyaoJiang1998/RAISE

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✨CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production

📝 Summary:
CharacterFlywheel is an iterative optimization process that enhances large language models for social chat applications through multiple generations of refinement, achieving significant improvements i...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01973
• PDF: https://arxiv.org/pdf/2603.01973

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✨Agentic Code Reasoning

📝 Summary:
LLM agents can perform code reasoning tasks like patch verification, fault localization, and code QA with improved accuracy through structured semi-formal reasoning that requires explicit premises and...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01896
• PDF: https://arxiv.org/pdf/2603.01896

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✨FireRed-OCR Technical Report

📝 Summary:
FireRed-OCR transforms general vision-language models into specialized OCR systems through structured data synthesis and progressive training strategies. AI-generated summary We present FireRed-OCR, a...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01840
• PDF: https://arxiv.org/pdf/2603.01840
• Github: https://github.com/FireRedTeam/FireRed-OCR

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✨MMR-Life: Piecing Together Real-life Scenes for Multimodal Multi-image Reasoning

📝 Summary:
MMR-Life is a new benchmark assessing multimodal large language models reasoning across real-life scenarios using diverse multi-image questions. It features 2,646 questions on 19,108 real-world images covering seven reasoning types. Top models like GPT-5 only achieve 58 percent accuracy, showing ...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02024
• PDF: https://arxiv.org/pdf/2603.02024
• Project Page: https://mmr-life-bench.github.io/
• Github: https://github.com/BugMakerzzz/MMR-Life

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Septzzz/MMR-Life

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✨CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification

📝 Summary:
CoVe is a post-training data synthesis framework that generates high-quality training trajectories for interactive tool-use agents by incorporating task constraints as verification mechanisms, achievi...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01940
• PDF: https://arxiv.org/pdf/2603.01940
• Project Page: https://cove-agent.github.io

🔹 Models citing this paper:
• https://huggingface.co/Zichen1024/CoVe-4B

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Zichen1024/CoVe-12k

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

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✨Learn Hard Problems During RL with Reference Guided Fine-tuning

📝 Summary:
Reference-Guided Fine-Tuning (ReGFT) addresses reward sparsity in reinforcement learning for mathematical reasoning by using human-written solutions to create guided training trajectories that improve...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01223
• PDF: https://arxiv.org/pdf/2603.01223

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✨Tool Verification for Test-Time Reinforcement Learning

📝 Summary:
Test-time reinforcement learning with tool verification addresses consensus bias in large reasoning models by using external validation to improve reward estimation and model stability. AI-generated s...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02203
• PDF: https://arxiv.org/pdf/2603.02203

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✨ArtLLM: Generating Articulated Assets via 3D LLM

📝 Summary:
ArtLLM generates articulated 3D assets from meshes using a 3D multimodal large language model that predicts part layouts and joints while synthesizing high-fidelity geometries. AI-generated summary Cr...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01142
• PDF: https://arxiv.org/pdf/2603.01142

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✨MicroVerse: A Preliminary Exploration Toward a Micro-World Simulation

📝 Summary:
Current video generation models struggle with microscale simulation tasks, prompting the development of MicroVerse, a specialized video generation model trained on expert-verified simulation data to a...

🔹 Publication Date: Published on Feb 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00585
• PDF: https://arxiv.org/pdf/2603.00585

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✨Recursive Think-Answer Process for LLMs and VLMs

📝 Summary:
Recursive Think-Answer Process enables iterative reasoning cycles that improve accuracy and reduce self-reflective errors in language and vision-language models through confidence-based reinforcement ...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02099
• PDF: https://arxiv.org/pdf/2603.02099
• Project Page: https://litcoderr.github.io/rtap_page/

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✨From Scale to Speed: Adaptive Test-Time Scaling for Image Editing

📝 Summary:
Image-CoT methods are extended to image editing with ADE-CoT, which improves efficiency and performance through adaptive resource allocation, edit-specific verification, and opportunistic stopping mec...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00141
• PDF: https://arxiv.org/pdf/2603.00141

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