✨AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules

📝 Summary:
AceFF is a new machine learning potential for small molecule drug discovery. It offers DFT-level accuracy with high speed, supporting essential elements and charged states. Validation shows it is state-of-the-art for organic molecules.

🔹 Publication Date: Published on Jan 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.00581
• PDF: https://arxiv.org/pdf/2601.00581
• Github: https://github.com/torchmd/torchmd-net

🔹 Models citing this paper:
• https://huggingface.co/Acellera/AceFF-2.0

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

For more data science resources:
✓ https://t.me/DataScienceT

#MachineLearning #DrugDiscovery #ComputationalChemistry #AIforScience #SmallMolecules

✨Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training

📝 Summary:
Muses is a training-free method for generating fantastic 3D creatures. It leverages 3D skeletal structures and graph-constrained reasoning to coherently design, compose, and assemble diverse elements. This approach achieves state-of-the-art visual fidelity and alignment with text descriptions.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03256
• PDF: https://arxiv.org/pdf/2601.03256
• Github: https://github.com/luhexiao/Muses

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

For more data science resources:
✓ https://t.me/DataScienceT

#3DGeneration #GenerativeAI #ComputerGraphics #AIArt #TrainingFreeAI

✨U-Net-Like Spiking Neural Networks for Single Image Dehazing

📝 Summary:
DehazeSNN introduces a U-Net-like Spiking Neural Network with an Orthogonal Leaky-Integrate-and-Fire Block for efficient image dehazing. It achieves competitive performance with reduced computational resources and a smaller model size.

🔹 Publication Date: Published on Dec 30, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23950
• PDF: https://arxiv.org/pdf/2512.23950
• Github: https://github.com/HaoranLiu507/DehazeSNN

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models

📝 Summary:
This paper presents a four-stage framework for AI in digital twins: modeling, mirroring, intervention, and autonomous management. It details how physics-informed AI and large language models empower proactive, self-improving digital twins, acknowledging key challenges.

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01321
• PDF: https://arxiv.org/pdf/2601.01321
• Github: https://github.com/rongzhou7/Awesome-Digital-Twin-AI/tree/main

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

For more data science resources:
✓ https://t.me/DataScienceT

#DigitalTwin #AI #LLM #WorldModels #PhysicsInformedAI

✨Mechanistic Interpretability of Large-Scale Counting in LLMs through a System-2 Strategy

📝 Summary:
LLMs struggle with large counting due to architectural limits. A System-2 inspired test-time strategy decomposes tasks into smaller parts, achieving high accuracy. This approach involves latent count computation, dedicated attention, and aggregation, overcoming model limitations.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02989
• PDF: https://arxiv.org/pdf/2601.02989

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

For more data science resources:
✓ https://t.me/DataScienceT

#LLM #MechanisticInterpretability #System2Strategy #AIResearch #NLP

✨ExposeAnyone: Personalized Audio-to-Expression Diffusion Models Are Robust Zero-Shot Face Forgery Detectors

📝 Summary:
ExposeAnyone is a self-supervised diffusion model for deepfake detection that personalizes to subjects and uses reconstruction errors to measure identity distance. It significantly outperforms prior methods on unseen manipulations, including Sora2 videos, and is robust to real-world corruptions.

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02359
• PDF: https://arxiv.org/pdf/2601.02359
• Github: https://mapooon.github.io/ExposeAnyonePage/

✨ Datasets citing this paper:
• https://huggingface.co/datasets/mapooon/S2CFP

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

For more data science resources:
✓ https://t.me/DataScienceT

#DeepfakeDetection #DiffusionModels #ComputerVision #AITechnology #ForgeryDetection

✨Unified Thinker: A General Reasoning Modular Core for Image Generation

📝 Summary:
Unified Thinker introduces a modular reasoning core for image generation, decoupling a Thinker from the generator. It uses reinforcement learning to optimize visual correctness, substantially improving image reasoning and generation quality.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03127
• PDF: https://arxiv.org/pdf/2601.03127

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

For more data science resources:
✓ https://t.me/DataScienceT

#ImageGeneration #AIResearch #ReinforcementLearning #DeepLearning #GenerativeAI

✨Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

📝 Summary:
Large reasoning models show multilingual latent reasoning, stronger in resource-rich languages but weaker in low-resource ones. Despite varying strength, their internal prediction evolution is consistent across languages, suggesting an English-centered latent reasoning pathway.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02996
• PDF: https://arxiv.org/pdf/2601.02996
• Github: https://github.com/cisnlp/multilingual-latent-reasoner

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨UniVideo: Unified Understanding, Generation, and Editing for Videos

📝 Summary:
UniVideo, a dual-stream framework combining a Multimodal Large Language Model and a Multimodal DiT, extends unified modeling to video generation and editing, achieving state-of-the-art performance and...

🔹 Publication Date: Published on Oct 9, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08377
• PDF: https://arxiv.org/pdf/2510.08377
• Project Page: https://congwei1230.github.io/UniVideo/
• Github: https://github.com/KwaiVGI/UniVideo

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

nature papers: 1400$

Q1 and  Q2 papers    900$

Q3 and Q4 papers   500$

Doctoral thesis (complete)    700$

M.S thesis         300$

paper simulation   200$

Contact me
https://t.me/m/-nTmpj5vYzNk

✨MindWatcher: Toward Smarter Multimodal Tool-Integrated Reasoning

📝 Summary:
MindWatcher is a tool-integrated reasoning agent using interleaved thinking and multimodal chain-of-thought. It autonomously coordinates diverse tools for complex tasks without human prompts. It outperforms larger models and provides agent training insights.

🔹 Publication Date: Published on Dec 29, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23412
• PDF: https://arxiv.org/pdf/2512.23412
• Github: https://github.com/TIMMY-CHAN/MindWatcher

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics

📝 Summary:
MDAgent2 enables automated molecular dynamics code generation and question answering through domain-adapted language models and a multi-agent runtime system. AI-generated summary Molecular dynamics (M...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02075
• PDF: https://arxiv.org/pdf/2601.02075
• Github: https://github.com/FredericVAN/PKU_MDAgent2

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Choreographing a World of Dynamic Objects

📝 Summary:
CHORD is a universal generative framework that extracts Lagrangian motion information from Eulerian video representations to synthesize diverse 4D dynamic scenes without requiring category-specific ru...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04194
• PDF: https://arxiv.org/pdf/2601.04194
• Project Page: https://yanzhelyu.github.io/chord/

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering for Enhanced Alignment and Reasoning

📝 Summary:
EpiQAL presents a novel benchmark for evaluating epidemiological reasoning in language models through three distinct subsets measuring factual recall, multi-step inference, and conclusion reconstructi...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03471
• PDF: https://arxiv.org/pdf/2601.03471

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models

📝 Summary:
Entropy-aware policy optimization method for reinforcement learning in flow matching models that improves exploration through SDE and ODE sampling strategies. AI-generated summary Recent reinforcement...

🔹 Publication Date: Published on Jan 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.00423
• PDF: https://arxiv.org/pdf/2601.00423
• Github: https://github.com/shengjun-zhang/VisualGRPO

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Agentic Rubrics as Contextual Verifiers for SWE Agents

📝 Summary:
Agentic Rubrics enable efficient and scalable verification for software engineering agents by creating context-aware checklists that outperform traditional methods while maintaining interpretability. ...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04171
• PDF: https://arxiv.org/pdf/2601.04171

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Klear: Unified Multi-Task Audio-Video Joint Generation

📝 Summary:
Klear addresses audio-video joint generation challenges through a unified model architecture, progressive multitask training, and large-scale dense-caption data construction, achieving superior alignm...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04151
• PDF: https://arxiv.org/pdf/2601.04151

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models

📝 Summary:
RedBench presents a unified dataset with standardized risk categorization for evaluating LLM vulnerabilities across multiple domains and attack types. AI-generated summary As large language models (LL...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03699
• PDF: https://arxiv.org/pdf/2601.03699
• Github: https://github.com/knoveleng/redeval

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Entropy-Adaptive Fine-Tuning: Resolving Confident Conflicts to Mitigate Forgetting

📝 Summary:
Supervised Fine-Tuning causes catastrophic forgetting due to 'Confident Conflicts.' Entropy-Adaptive Fine-Tuning EAFT uses token-level entropy to distinguish uncertainty from knowledge conflict. EAFT suppresses conflicting gradients, mitigating forgetting while matching performance.

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02151
• PDF: https://arxiv.org/pdf/2601.02151
• Project Page: https://ymxyll.github.io/EAFT/
• Github: https://ymxyll.github.io/EAFT/

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Benchmark^2: Systematic Evaluation of LLM Benchmarks

📝 Summary:
Researchers developed Benchmark^2, a framework with three metrics to evaluate benchmark quality for large language models, revealing significant variations in existing benchmarks and enabling more eff...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03986
• PDF: https://arxiv.org/pdf/2601.03986

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research

✨ThinkRL-Edit: Thinking in Reinforcement Learning for Reasoning-Centric Image Editing

📝 Summary:
ThinkRL-Edit enhances reasoning-centric image editing through reinforcement learning by expanding visual reasoning exploration beyond denoising stochasticity and using unbiased reward strategies. AI-g...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03467
• PDF: https://arxiv.org/pdf/2601.03467

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

For more data science resources:
✓ https://t.me/DataScienceT

#AI #DataScience #MachineLearning #HuggingFace #Research