✨EVATok: Adaptive Length Video Tokenization for Efficient Visual Autoregressive Generation

📝 Summary:
EVATok is a framework for efficient video tokenization that adapts token assignment based on video content, improving reconstruction quality and generation efficiency through learned routers and adapt...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12267
• PDF: https://arxiv.org/pdf/2603.12267
• Project Page: https://silentview.github.io/EVATok/
• Github: https://github.com/HKU-MMLab/EVATok

🔹 Models citing this paper:
• https://huggingface.co/YuuTennYi/EVATok

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DIVE: Scaling Diversity in Agentic Task Synthesis for Generalizable Tool Use

📝 Summary:
Training Qwen3-8B on DIVE data improves performance across out-of-distribution benchmarks, with diversity scaling outperforming quantity scaling even with less data. AI-generated summary Recent work s...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11076
• PDF: https://arxiv.org/pdf/2603.11076
• Project Page: https://sheep333c.github.io/DIVE/
• Github: https://github.com/sheep333c/DIVE

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨EmbTracker: Traceable Black-box Watermarking for Federated Language Models

📝 Summary:
EmbTracker is a server-side black-box watermarking framework for federated language models that provides client-level traceability through unique identity-specific watermarks embedded via backdoor det...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12089
• PDF: https://arxiv.org/pdf/2603.12089

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Mobile-GS: Real-time Gaussian Splatting for Mobile Devices

📝 Summary:
Mobile-GS enables real-time 3D Gaussian Splatting rendering on mobile devices through depth-aware order-independent rendering, neural view-dependent enhancement, and compression techniques. AI-generat...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11531
• PDF: https://arxiv.org/pdf/2603.11531
• Project Page: https://xiaobiaodu.github.io/mobile-gs-project/
• Github: https://github.com/xiaobiaodu/mobile-gs

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DVD: Deterministic Video Depth Estimation with Generative Priors

📝 Summary:
DVD adapts pre-trained video diffusion models into deterministic single-pass depth regressors using structural anchors, latent manifold rectification, and global affine coherence. This framework achieves state-of-the-art zero-shot video depth estimation with significantly less data, overcoming li...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12250
• PDF: https://arxiv.org/pdf/2603.12250
• Project Page: https://dvd-project.github.io/
• Github: https://github.com/EnVision-Research/DVD

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Automatic Generation of High-Performance RL Environments

📝 Summary:
Automated framework generates high-performance reinforcement learning environments through prompt-based translation and verification, achieving significant speedups over existing implementations while...

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12145
• PDF: https://arxiv.org/pdf/2603.12145

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition System

📝 Summary:
FireRedASR2S is an industrial-grade ASR system integrating unified modules for speech recognition, voice activity detection, language identification, and punctuation prediction, achieving state-of-the...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10420
• PDF: https://arxiv.org/pdf/2603.10420
• Project Page: https://github.com/FireRedTeam/FireRedASR2S
• Github: https://github.com/FireRedTeam/FireRedASR2S

🔹 Models citing this paper:
• https://huggingface.co/FireRedTeam/FireRedVAD
• https://huggingface.co/FireRedTeam/FireRedASR2-AED
• https://huggingface.co/FireRedTeam/FireRedASR2-LLM

✨ Spaces citing this paper:
• https://huggingface.co/spaces/FireRedTeam/FireRedASR2S

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data

📝 Summary:
Accent Vector enables controllable accent manipulation in multilingual TTS systems through fine-tuning on native speech from different languages and computing task vectors that capture accent characte...

🔹 Publication Date: Published on Mar 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07534
• PDF: https://arxiv.org/pdf/2603.07534

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨The Curse and Blessing of Mean Bias in FP4-Quantized LLM Training

📝 Summary:
LLM anisotropy caused by rank-one mean bias in low-bit training can be stabilized through mean subtraction, recovering performance while enabling efficient hardware deployment. AI-generated summary La...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10444
• PDF: https://arxiv.org/pdf/2603.10444

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨4DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Video

📝 Summary:
4DEquine is a new framework for 4D equine reconstruction from monocular video. It disentangles motion using spatio-temporal transformers and appearance with 3D Gaussian avatars. Training on synthetic data, it achieves state-of-the-art results on real-world datasets.

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10125
• PDF: https://arxiv.org/pdf/2603.10125
• Project Page: https://luoxue-star.github.io/4DEquine_Project_Page/
• Github: https://github.com/luoxue-star/4DEquine

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

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#ComputerVision #4DReconstruction #DeepLearning #Equine #AI

✨Training Language Models via Neural Cellular Automata

📝 Summary:
This paper introduces using Neural Cellular Automata NCA to generate synthetic data for pre-pre-training language models, addressing natural language limitations. This approach improves performance, accelerates convergence, and transfers to reasoning tasks, often outperforming extensive natural l...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10055
• PDF: https://arxiv.org/pdf/2603.10055

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

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#AI #LanguageModels #NeuralCellularAutomata #SyntheticData #NLP

✨XSkill: Continual Learning from Experience and Skills in Multimodal Agents

📝 Summary:
XSkill is a dual-stream framework for continual learning in multimodal agents. It extracts and retrieves knowledge from visual observations, consolidating experiences and skills. This improves tool use efficiency, reasoning, and zero-shot generalization.

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12056
• PDF: https://arxiv.org/pdf/2603.12056
• Project Page: https://xskill-agent.github.io/xskill_page/
• Github: https://github.com/XSkill-Agent/XSkill

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

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#ContinualLearning #MultimodalAI #AIagents #MachineLearning #Robotics

✨Neural Field Thermal Tomography: A Differentiable Physics Framework for Non-Destructive Evaluation

📝 Summary:
NeFTY is a new differentiable physics framework that reconstructs 3D material properties from temperature measurements. It uses continuous neural fields and hard constraints, overcoming prior limitations and accurately locating subsurface defects.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11045
• PDF: https://arxiv.org/pdf/2603.11045
• Project Page: https://cab-lab-princeton.github.io/nefty/
• Github: https://cab-lab-princeton.github.io/nefty/

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

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#NeuralFields #DifferentiablePhysics #NDE #MaterialScience #DeepLearning

✨Causal Attribution of Coastal Water Clarity Degradation to Nickel Processing Expansion at the Indonesia Morowali Industrial Park, Sulawesi

📝 Summary:
Satellite data and causal analysis established that Indonesia Morowali Industrial Park expansion caused significant coastal water clarity degradation. This impact, linked to battery-grade nickel production, threatens marine biodiversity and coral reefs.

🔹 Publication Date: Published on Mar 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07331
• PDF: https://arxiv.org/pdf/2603.07331
• Github: https://github.com/sandyherho/supplMorowaliOcean

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#EnvironmentalScience #CoastalDegradation #NickelMining #MarineConservation #Indonesia

✨A Mixed Diet Makes DINO An Omnivorous Vision Encoder

📝 Summary:
The Omnivorous Vision Encoder learns modality-agnostic features by aligning multi-modal scene inputs and distilling semantics from a frozen teacher model. This resolves poor cross-modal alignment in existing encoders, yielding consistent, powerful embeddings for various modalities.

🔹 Publication Date: Published on Feb 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.24181
• PDF: https://arxiv.org/pdf/2602.24181

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

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#MultimodalAI #ComputerVision #DeepLearning #SelfSupervisedLearning #AIResearch

✨Dr. SHAP-AV: Decoding Relative Modality Contributions via Shapley Attribution in Audio-Visual Speech Recognition

📝 Summary:
Dr. SHAP-AV uses Shapley values to analyze audio-visual speech recognition modality contributions. Findings show models shift toward visual under noise but maintain a persistent audio bias. This method serves as a key diagnostic tool for AVSR.

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12046
• PDF: https://arxiv.org/pdf/2603.12046
• Project Page: https://umbertocappellazzo.github.io/Dr-SHAP-AV/
• Github: https://github.com/umbertocappellazzo/Dr-SHAP-AV

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

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#AVSR #ShapleyValues #ExplainableAI #MultimodalAI #SpeechRecognition

✨Simple Recipe Works: Vision-Language-Action Models are Natural Continual Learners with Reinforcement Learning

📝 Summary:
Contrary to established belief, simple sequential fine-tuning with low-rank adaptation is highly effective for continual reinforcement learning in large Vision-Language-Action models. It achieves excellent plasticity and avoids catastrophic forgetting, often outperforming complex methods.

🔹 Publication Date: Published on Mar 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11653
• PDF: https://arxiv.org/pdf/2603.11653

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

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#ReinforcementLearning #ContinualLearning #VLAmodels #AI #MachineLearning

✨HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement

📝 Summary:
HyPER-GAN is a lightweight U-Net based model for real-time photorealism enhancement. Its hybrid training strategy, using real-world patches, improves visual realism, semantic consistency, and inference speed over state-of-the-art methods.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10604
• PDF: https://arxiv.org/pdf/2603.10604
• Github: https://github.com/stefanos50/HyPER-GAN

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

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#GAN #ComputerVision #DeepLearning #ImageProcessing #Photorealism

✨PACED: Distillation at the Frontier of Student Competence

📝 Summary:
PACED optimizes distillation by focusing training on a student competence frontier using a Beta kernel weighting. Derived from gradient analysis, this avoids wasted compute at extremes, boosting distillation and self-distillation performance.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11178
• PDF: https://arxiv.org/pdf/2603.11178

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

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#KnowledgeDistillation #DeepLearning #ModelOptimization #AIResearch #ComputeEfficiency

✨SurvHTE-Bench: A Benchmark for Heterogeneous Treatment Effect Estimation in Survival Analysis

📝 Summary:
SurvHTE-Bench is the first comprehensive benchmark for estimating heterogeneous treatment effects with censored survival data. It offers synthetic, semi-synthetic, and real-world datasets for rigorous and reproducible evaluation of causal survival methods.

🔹 Publication Date: Published on Mar 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.05483
• PDF: https://arxiv.org/pdf/2603.05483
• Github: https://github.com/Shahriarnz14/SurvHTE-Bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/snoroozi/SurvHTE-Bench

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Meta-Reinforcement Learning with Self-Reflection for Agentic Search

📝 Summary:
MR-Search is a meta-reinforcement learning approach for agentic search that uses self-reflection. It conditions on past episodes to adapt search strategies and improve in-context exploration. This method shows strong generalization and significant performance gains across various benchmarks.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11327
• PDF: https://arxiv.org/pdf/2603.11327

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

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#AI #DataScience #MachineLearning #HuggingFace #Research