✨Spectrum Matching: a Unified Perspective for Superior Diffusability in Latent Diffusion

📝 Summary:
Variational autoencoders' learnability in latent diffusion is enhanced through spectrum matching techniques that align power-law spectral densities and preserve frequency semantics during encoding and...

🔹 Publication Date: Published on Mar 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14645
• PDF: https://arxiv.org/pdf/2603.14645

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✨POLCA: Stochastic Generative Optimization with LLM

📝 Summary:
POLCA is an LLM-based framework for stochastic generative optimization of complex systems. It achieves robust, efficient convergence by managing exploration and stochasticity, outperforming state-of-the-art methods.

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14769
• PDF: https://arxiv.org/pdf/2603.14769
• Github: https://github.com/rlx-lab/POLCA

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✨AgentProcessBench: Diagnosing Step-Level Process Quality in Tool-Using Agents

📝 Summary:
AgentProcessBench introduces the first benchmark for evaluating step-level effectiveness in tool-augmented AI agents. It uses human-annotated trajectories to diagnose agent failures, revealing challenges in distinguishing errors and the value of process-level signals for improving agent performance.

🔹 Publication Date: Published on Mar 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14465
• PDF: https://arxiv.org/pdf/2603.14465
• Project Page: https://rucbm.github.io/AgentProcessBench-Homepage/
• Github: https://github.com/RUCBM/AgentProcessBench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/LulaCola/AgentProcessBench

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✨FlashSampling: Fast and Memory-Efficient Exact Sampling

📝 Summary:
FlashSampling enables efficient categorical sampling by fusing the operation into the language model head matmul, eliminating memory overhead and reducing decoding time by up to 19%. AI-generated summ...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15854
• PDF: https://arxiv.org/pdf/2603.15854
• Project Page: https://github.com/FlashSampling/FlashSampling
• Github: https://github.com/FlashSampling/FlashSampling

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✨Measuring Primitive Accumulation: An Information-Theoretic Approach to Capitalist Enclosure in PIK2, Indonesia

📝 Summary:
Large-scale land enclosure for speculative mega-development constitutes a non-equilibrium spatial process whose velocity, topology, and irreversibility remain poorly quantified. We study the Pantai In...

🔹 Publication Date: Published on Mar 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.13715
• PDF: https://arxiv.org/pdf/2603.13715
• Github: https://github.com/sandyherho/supplPIK2LULC

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✨Recursive Language Models Meet Uncertainty: The Surprising Effectiveness of Self-Reflective Program Search for Long Context

📝 Summary:
Language models struggle with long-context handling, but a new framework called SRLM improves performance by incorporating uncertainty-aware self-reflection to guide programmatic context interaction, ...

🔹 Publication Date: Published on Mar 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15653
• PDF: https://arxiv.org/pdf/2603.15653

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✨Online Experiential Learning for Language Models

📝 Summary:
Online Experiential Learning enables continuous improvement of language models through deployment experience by extracting and consolidating experiential knowledge via on-policy distillation. AI-gener...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16856
• PDF: https://arxiv.org/pdf/2603.16856
• Project Page: https://github.com/microsoft/LMOps/tree/main/oel
• Github: https://github.com/microsoft/LMOps/tree/main/oel

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✨Demystifing Video Reasoning

📝 Summary:
Diffusion-based video models demonstrate reasoning capabilities through denoising steps rather than frame sequences, exhibiting behaviors like working memory, self-correction, and perception-before-ac...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16870
• PDF: https://arxiv.org/pdf/2603.16870
• Project Page: https://www.wruisi.com/demystifying_video_reasoning/

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✨WorldCam: Interactive Autoregressive 3D Gaming Worlds with Camera Pose as a Unifying Geometric Representation

📝 Summary:
WorldCam uses camera pose as a unifying geometric representation for interactive 3D gaming worlds. This enables precise action control via a physics-based space and long-term 3D consistency by retrieving observations with global poses.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16871
• PDF: https://arxiv.org/pdf/2603.16871
• Project Page: https://cvlab-kaist.github.io/WorldCam/
• Github: https://github.com/cvlab-kaist/WorldCam

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✨SocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Models

📝 Summary:
SocialOmni presents a benchmark for evaluating social interactivity in omni-modal large language models across speaker identification, interruption timing, and natural interruption generation, reveali...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16859
• PDF: https://arxiv.org/pdf/2603.16859
• Project Page: https://huggingface.co/datasets/alexisty/SocialOmni
• Github: https://github.com/MAC-AutoML/SocialOmni

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✨Reliable Reasoning in SVG-LLMs via Multi-Task Multi-Reward Reinforcement Learning

📝 Summary:
CTRL-S framework enhances SVG generation through chain-of-thought reasoning and multi-reward optimization, achieving better structural coherence and visual fidelity. AI-generated summary With the rapi...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16189
• PDF: https://arxiv.org/pdf/2603.16189
• Github: https://github.com/hmwang2002/CTRL-S

✨ Datasets citing this paper:
• https://huggingface.co/datasets/InternSVG/SVG-Sophia

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✨SegviGen: Repurposing 3D Generative Model for Part Segmentation

📝 Summary:
SegviGen repurposes pretrained 3D generative models for efficient 3D part segmentation using distinctive part colorization, achieving superior performance with minimal labeled data. AI-generated summa...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16869
• PDF: https://arxiv.org/pdf/2603.16869
• Project Page: https://fenghora.github.io/SegviGen-Page/
• Github: https://fenghora.github.io/SegviGen-Page/

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✨MiroThinker-1.7 & H1: Towards Heavy-Duty Research Agents via Verification

📝 Summary:
MiroThinker-1.7 and MiroThinker-H1 are research agents that enhance complex reasoning through structured planning, contextual reasoning, and tool interaction, with MiroThinker-H1 incorporating verific...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15726
• PDF: https://arxiv.org/pdf/2603.15726
• Project Page: https://www.miromind.ai/

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✨M^3: Dense Matching Meets Multi-View Foundation Models for Monocular Gaussian Splatting SLAM

📝 Summary:
Multi-view foundation model enhanced with matching head and monocular Gaussian splatting SLAM achieves improved pose estimation and scene reconstruction accuracy. AI-generated summary Streaming recons...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16844
• PDF: https://arxiv.org/pdf/2603.16844
• Project Page: https://city-super.github.io/M3/
• Github: https://github.com/InternRobotics/M3

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✨Learning Human-Object Interaction for 3D Human Pose Estimation from LiDAR Point Clouds

📝 Summary:
Human-Object Interaction Learning framework addresses challenges in 3D human pose estimation from LiDAR point clouds by mitigating spatial ambiguity and class imbalance through contrastive learning an...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16343
• PDF: https://arxiv.org/pdf/2603.16343
• Project Page: https://hoil-release.github.io/

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✨Polyglot-Lion: Efficient Multilingual ASR for Singapore via Balanced Fine-Tuning of Qwen3-ASR

📝 Summary:
Polyglot-Lion, a compact multilingual ASR model family for Singapore's linguistic diversity, achieves competitive performance with significantly reduced training cost and improved inference speed thro...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16184
• PDF: https://arxiv.org/pdf/2603.16184
• Project Page: https://knoveleng.github.io/polyglot-lion/
• Github: https://github.com/knoveleng/polyglot-lion

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✨CCTU: A Benchmark for Tool Use under Complex Constraints

📝 Summary:
Solving problems through tool use under explicit constraints constitutes a highly challenging yet unavoidable scenario for large language models (LLMs), requiring capabilities such as function calling...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.15309
• PDF: https://arxiv.org/pdf/2603.15309
• Github: https://github.com/Junjie-Ye/CCTU

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Junjie-Ye/CCTU

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✨Efficient Reasoning on the Edge

📝 Summary:
Lightweight reasoning in small language models is enabled through LoRA adapters, budget forcing via reinforcement learning, parallel test-time scaling, and dynamic adapter switching under strict resou...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16867
• PDF: https://arxiv.org/pdf/2603.16867
• Project Page: https://qualcomm-ai-research.github.io/llm-reasoning-on-edge/

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✨MolmoB0T: Large-Scale Simulation Enables Zero-Shot Manipulation

📝 Summary:
Zero-shot sim-to-real transfer is demonstrated for robotic manipulation using large-scale synthetic data and vision-language models with flow-matching action heads, achieving high success rates withou...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16861
• PDF: https://arxiv.org/pdf/2603.16861
• Project Page: https://allenai.org/blog/molmobot-robot-manipulation

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✨OneWorld: Taming Scene Generation with 3D Unified Representation Autoencoder

📝 Summary:
OneWorld enables 3D scene generation by performing diffusion in a unified 3D representation space using a 3D Unified Representation Autoencoder and specialized consistency losses. AI-generated summary...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16099
• PDF: https://arxiv.org/pdf/2603.16099
• Github: https://github.com/SensenGao/OneWorld

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