✨Chain-of-Trajectories: Unlocking the Intrinsic Generative Optimality of Diffusion Models via Graph-Theoretic Planning

📝 Summary:
Chain-of-Trajectories framework enables deliberative planning for diffusion models by using Diffusion DNA to dynamically allocate computational resources based on denoising difficulty. AI-generated su...

🔹 Publication Date: Published on Mar 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14704
• PDF: https://github.com/UnicomAI/CoTj/blob/main/CoTj_v20260305.pdf
• Github: https://github.com/UnicomAI/CoTj

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✨Mixture of Style Experts for Diverse Image Stylization

📝 Summary:
StyleExpert introduces a Mixture of Experts architecture for image stylization. It uses a unified style encoder and gating mechanism to handle diverse styles across semantic levels. This preserves semantics and material details better than existing methods.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16649
• PDF: https://arxiv.org/pdf/2603.16649
• Project Page: https://hh-lg.github.io/StyleExpert-Page/
• Github: https://github.com/HVision-NKU/StyleExpert

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✨Omnilingual MT: Machine Translation for 1,600 Languages

📝 Summary:
Omnilingual MT OMT is the first system to support over 1,600 languages. It uses specialized smaller LLMs 1B-8B to outperform 70B baselines, achieving high-quality translation and coherent generation in low-compute settings.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16309
• PDF: https://arxiv.org/pdf/2603.16309

✨ Datasets citing this paper:
• https://huggingface.co/datasets/facebook/bouquet

✨ Spaces citing this paper:
• https://huggingface.co/spaces/facebook/bouquet

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✨Sparking Scientific Creativity via LLM-Driven Interdisciplinary Inspiration

📝 Summary:
Idea-Catalyst is a framework that supports interdisciplinary research by identifying insights across domains to enhance creative reasoning in scientific discovery. AI-generated summary Despite interdi...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12226
• PDF: https://arxiv.org/pdf/2603.12226
• Project Page: https://pkargupta.github.io/idea_catalyst.html
• Github: https://pkargupta.github.io/idea_catalyst.html

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✨HistoAtlas: A Pan-Cancer Morphology Atlas Linking Histomics to Molecular Programs and Clinical Outcomes

📝 Summary:
HistoAtlas is a pan-cancer computational map linking 38 H&E histomic features to patient outcomes and molecular profiles across 21 cancer types. It reveals new biology and allows biomarker discovery from routine slides.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16587
• PDF: https://arxiv.org/pdf/2603.16587
• Project Page: https://histoatlas.com
• Github: https://github.com/HistoAtlas/HistoAtlas

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✨SparkVSR: Interactive Video Super-Resolution via Sparse Keyframe Propagation

📝 Summary:
SparkVSR offers interactive video super-resolution using sparse keyframes as user control. It propagates high-resolution keyframe information through the video, guided by motion, enhancing temporal consistency and restoration quality.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16864
• PDF: https://arxiv.org/pdf/2603.16864
• Project Page: https://sparkvsr.github.io/
• Github: https://github.com/taco-group/SparkVSR

🔹 Models citing this paper:
• https://huggingface.co/JiongzeYu/SparkVSR

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✨MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games

📝 Summary:
MEMO, a memory-augmented model context optimization framework, improves multi-agent LLM game performance and stability through retained insights and exploratory prompt evolution with uncertainty-aware...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09022
• PDF: https://arxiv.org/pdf/2603.09022
• Project Page: https://yunfeixie233.github.io/MEMO/
• Github: https://github.com/openverse-ai/MEMO

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✨BERTology of Molecular Property Prediction

📝 Summary:
Researchers systematically investigate how dataset size, model size, and standardization impact chemical language model performance in molecular property prediction. This study provides numerical evidence to understand mechanisms affecting performance and resolve inconsistent literature results.

🔹 Publication Date: Published on Mar 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.13627
• PDF: https://arxiv.org/pdf/2603.13627
• Github: https://github.com/molssi-ai/bertology

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✨V-Co: A Closer Look at Visual Representation Alignment via Co-Denoising

📝 Summary:
Pixel-space diffusion models can be enhanced through visual co-denoising techniques that incorporate pretrained visual features, with systematic analysis revealing key architectural and training compo...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16792
• PDF: https://arxiv.org/pdf/2603.16792

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

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✨ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation

📝 Summary:
W h i l e M u l t i m o d a l L a r g e L a n g u a g e M o d e l s ( M L L M s ) s h o w p r o m i s i n g p e r f o r m a n c e i n a u t o m a t e d e l e c t r o c a r d i o g r a m i n t e r p r ...

🔹 Publication Date: Published on Mar 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.14326
• PDF: https://arxiv.org/pdf/2603.14326

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Jwoo5/ECG-Reasoning-Benchmark

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✨Residual Stream Duality in Modern Transformer Architectures

📝 Summary:
The residual stream in Transformers can be viewed through a two-axis framework where sequence position and layer depth provide different pathways for information flow, with causal depth-wise residual ...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16039
• PDF: https://arxiv.org/pdf/2603.16039
• Project Page: https://github.com/yifanzhang-pro/residual-stream-duality
• Github: https://github.com/yifanzhang-pro/residual-stream-duality

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✨ARISE: Agent Reasoning with Intrinsic Skill Evolution in Hierarchical Reinforcement Learning

📝 Summary:
A hierarchical reinforcement learning framework named ARISE employs a skill management system to improve mathematical reasoning in language models through reusable strategies and structured skill libr...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16060
• PDF: https://arxiv.org/pdf/2603.16060
• Github: https://github.com/Skylanding/ARISE

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✨MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models

📝 Summary:
MDM-Prime-v2 enhances masked diffusion language models with Binary Encoding and Index Shuffling. It is 21.8 times more compute-efficient than autoregressive models, achieving significantly better perplexity and zero-shot accuracy.

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16077
• PDF: https://arxiv.org/pdf/2603.16077
• Project Page: https://chen-hao-chao.github.io/mdm-prime-v2/
• Github: https://github.com/chen-hao-chao/mdm-prime-v2

🔹 Models citing this paper:
• https://huggingface.co/chen-hao-chao/mdm-prime-v2-c4
• https://huggingface.co/chen-hao-chao/mdm-prime-v2-slimpajama

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✨Mamba: Linear-Time Sequence Modeling with Selective State Spaces

📝 Summary:
Mamba is a novel SSM that outperforms Transformers by enabling content-based reasoning through selective state spaces. It offers 5x faster inference, linear scaling, and achieves state-of-the-art results across language, audio, and genomics, even matching larger Transformers.

🔹 Publication Date: Published on Dec 1, 2023

🔹 Paper Links:
• arXiv Page: https://arxivexplained.com/papers/mamba-linear-time-sequence-modeling-with-selective-state-spaces
• PDF: https://arxiv.org/pdf/2312.00752
• Github: https://github.com/state-spaces/mamba

🔹 Models citing this paper:
• https://huggingface.co/tiiuae/falcon-mamba-7b
• https://huggingface.co/state-spaces/mamba-2.8b-slimpj
• https://huggingface.co/tiiuae/falcon-mamba-7b-instruct

✨ Datasets citing this paper:
• https://huggingface.co/datasets/huaXiaKyrie/up
• https://huggingface.co/datasets/Sherirto/BD4UI

✨ Spaces citing this paper:
• https://huggingface.co/spaces/FallnAI/Quantize-HF-Models
• https://huggingface.co/spaces/openfree/LLM_Quantization
• https://huggingface.co/spaces/seawolf2357/LLM_Quantization

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✨Unified Spatio-Temporal Token Scoring for Efficient Video VLMs

📝 Summary:
STTS is a lightweight module for efficiently pruning vision tokens across vision transformer and language models in video VLMs. It achieves 62% efficiency gains with only a 0.7% performance drop by learning spatio-temporal token scoring without text conditioning.

🔹 Publication Date: Published on Mar 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.18004
• PDF: https://arxiv.org/pdf/2603.18004
• Github: https://github.com/allenai/STTS

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✨MosaicMem: Hybrid Spatial Memory for Controllable Video World Models

📝 Summary:
Video diffusion models use hybrid spatial memory to maintain consistency under camera motion and enable long-term scene editing and navigation. AI-generated summary Video diffusion models are moving b...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.17117
• PDF: https://arxiv.org/pdf/2603.17117
• Project Page: https://mosaicmem.github.io/mosaicmem/
• Github: https://mosaicmem.github.io/mosaicmem/

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✨Stereo World Model: Camera-Guided Stereo Video Generation

📝 Summary:
StereoWorld is a camera-conditioned stereo world model that generates stereo videos end-to-end using RGB modality while maintaining geometric consistency and efficiency through novel attention mechani...

🔹 Publication Date: Published on Mar 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.17375
• PDF: https://arxiv.org/pdf/2603.17375
• Project Page: https://sunyangtian.github.io/StereoWorld-web/
• Github: https://github.com/SunYangtian/StereoWorld

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✨When AI Navigates the Fog of War

📝 Summary:
Large language models demonstrate varying capabilities in reasoning about unfolding geopolitical conflicts, showing strategic realism in structured settings but inconsistent performance in complex pol...

🔹 Publication Date: Published on Mar 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.16642
• PDF: https://arxiv.org/pdf/2603.16642
• Project Page: https://www.war-forecast-arena.com/
• Github: https://github.com/xirui-li/war-test

✨ Datasets citing this paper:
• https://huggingface.co/datasets/AIcell/war-test-dataset

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

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