📚 Professional Academic Writing & Simulation Services

Looking for high-quality academic assistance? We specialize in research papers, theses, and simulations tailored to your needs. All work is original, plagiarism-free, and aligned with top journal standards. Prices are competitive and flexible—contact us for custom quotes!

https://t.me/DataScienceY

✨Efficient Guided Generation for Large Language Models

📝 Summary:
This paper introduces an efficient method to guide large language model text generation. It uses regular expressions and context-free grammars with minimal added overhead, making guided generation practical.

🔹 Publication Date: Published on Jul 19, 2023

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2307.09702
• PDF: https://arxiv.org/pdf/2307.09702
• Github: https://github.com/normal-computing/outlines

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

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

#LLMs #TextGeneration #NLP #AI #DeepLearning

✨MADD: Multi-Agent Drug Discovery Orchestra

📝 Summary:
MADD is a multi-agent system integrating LLMs and specialized models to enhance hit identification in drug discovery. It builds customized pipelines from natural language queries, demonstrating superior performance and accessibility for researchers.

🔹 Publication Date: Published on Nov 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.08217
• PDF: https://arxiv.org/pdf/2511.08217
• Github: https://github.com/sb-ai-lab/MADD

✨ Datasets citing this paper:
• https://huggingface.co/datasets/ITMO-NSS/MADD_Benchmark_and_results

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

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

#DrugDiscovery #MultiAgentSystems #LLMs #AI #AIforScience

✨Adapting Web Agents with Synthetic Supervision

📝 Summary:
SynthAgent enhances web agent adaptation by improving synthetic data quality. It refines synthesized tasks and cleans collected trajectories to prevent hallucinations and noise. This dual refinement approach enables better performance on new websites.

🔹 Publication Date: Published on Nov 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.06101
• PDF: https://arxiv.org/pdf/2511.06101
• Project Page: https://github.com/aiming-lab/SynthAgent
• Github: https://github.com/aiming-lab/SynthAgent

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

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

#WebAgents #SyntheticData #MachineLearning #AIResearch #DataQuality

✨Motif 2 12.7B technical report

📝 Summary:
Motif-2-12.7B is an efficient LLM combining Grouped Differential Attention and system-level optimizations. It achieves competitive performance across diverse benchmarks with a smaller model size.

🔹 Publication Date: Published on Nov 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07464
• PDF: https://arxiv.org/pdf/2511.07464

🔹 Models citing this paper:
• https://huggingface.co/Motif-Technologies/optimizer
• https://huggingface.co/Motif-Technologies/Motif-2-12.7B-Instruct
• https://huggingface.co/Motif-Technologies/Motif-2-12.7B-Base

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

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

#LLM #AI #DeepLearning #EfficientAI #AttentionMechanisms

✨Depth Anything 3: Recovering the Visual Space from Any Views

📝 Summary:
Depth Anything 3 DA3 predicts spatially consistent geometry from any visual inputs, even without known camera poses. It uses a plain transformer backbone and a singular depth-ray prediction target. DA3 achieves new state-of-the-art results on a visual geometry benchmark, outperforming previous mo...

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10647
• PDF: https://arxiv.org/pdf/2511.10647

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

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

#ComputerVision #DepthEstimation #AIResearch #Transformers #3DReconstruction

✨MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples

📝 Summary:
MuSc-V2 framework improves zero-shot anomaly detection by leveraging mutual scoring and similarity aggregation in both 2D and 3D data, achieving significant performance gains over existing benchmarks....

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10047
• PDF: https://arxiv.org/pdf/2511.10047

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨UniVA: Universal Video Agent towards Open-Source Next-Generation Video Generalist

📝 Summary:
UniVA is an open-source multi-agent framework that unifies video understanding, segmentation, editing, and generation. It uses a Plan-and-Act architecture with hierarchical memory to enable complex, iterative video workflows. This system aims to advance agentic video intelligence.

🔹 Publication Date: Published on Nov 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.08521
• PDF: https://arxiv.org/pdf/2511.08521
• Project Page: https://univa.online/
• Github: https://github.com/univa-agent/univa

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

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

#VideoAI #AIagents #GenerativeAI #ComputerVision #OpenSource

✨Black-Box On-Policy Distillation of Large Language Models

📝 Summary:
Generative Adversarial Distillation GAD is a new black-box on-policy method for distilling LLMs. GAD trains a student generator and a discriminator for adaptive feedback, surpassing traditional distillation. It enables student LLMs to perform comparably to proprietary teachers.

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10643
• PDF: https://arxiv.org/pdf/2511.10643

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

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

#LLMs #AIDistillation #MachineLearning #GenerativeAI #DeepLearning

✨AlphaResearch: Accelerating New Algorithm Discovery with Language Models

📝 Summary:
AlphaResearch is an autonomous agent that discovers new algorithms using a dual research environment. It achieved a 2/8 win rate against human researchers and found a best-of-known solution for the packing circles problem, showing LLMs potential for algorithm discovery.

🔹 Publication Date: Published on Nov 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.08522
• PDF: https://arxiv.org/pdf/2511.08522
• Github: https://github.com/answers111/alpha-research

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

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

#AlgorithmDiscovery #LLMs #AIResearch #AutonomousAgents #MachineLearning

✨Music Flamingo: Scaling Music Understanding in Audio Language Models

📝 Summary:
Music Flamingo, a large audio-language model, advances music understanding through fine-tuning on a rich dataset and post-training with novel methods, achieving state-of-the-art results across various...

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10289
• PDF: https://arxiv.org/pdf/2511.10289

🔹 Models citing this paper:
• https://huggingface.co/nvidia/music-flamingo-hf

✨ Spaces citing this paper:
• https://huggingface.co/spaces/nvidia/music-flamingo

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨Superpositional Gradient Descent: Harnessing Quantum Principles for Model Training

📝 Summary:
Superpositional Gradient Descent SGD is a new quantum-inspired optimizer. It uses quantum superposition to enhance gradient updates, leading to faster convergence and lower final loss in LLM training than AdamW.

🔹 Publication Date: Published on Nov 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.01918
• PDF: https://arxiv.org/pdf/2511.01918
• Github: https://github.com/The-Aqua-Labs/Superpositional-Gradient-Descent

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

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

#MachineLearning #AI #LLM #QuantumInspired #Optimization

✨One Small Step in Latent, One Giant Leap for Pixels: Fast Latent Upscale Adapter for Your Diffusion Models

📝 Summary:
LUA performs efficient super-resolution directly in diffusion models' latent space. This lightweight module enables faster, high-quality image synthesis by upscaling before VAE decoding, cutting time versus pixel-space methods, and generalizing across VAEs.

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10629
• PDF: https://arxiv.org/pdf/2511.10629

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

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

#DiffusionModels #SuperResolution #LatentSpace #ImageGeneration #AIResearch

✨Benchmarking Diversity in Image Generation via Attribute-Conditional Human Evaluation

📝 Summary:
This paper introduces a framework to robustly evaluate diversity in text-to-image models. It uses a novel human evaluation template, curated prompts with variation factors, and systematic analysis of image embeddings to rank models and identify diversity weaknesses.

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10547
• PDF: https://arxiv.org/pdf/2511.10547

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

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

#ImageGeneration #TextToImage #AIDiversity #Benchmarking #HumanEvaluation

✨Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following

📝 Summary:
AdvancedIF benchmark and RIFL pipeline improve instruction-following capabilities in large language models by using expert-curated rubrics and reinforcement learning techniques. AI-generated summary R...

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10507
• PDF: https://arxiv.org/pdf/2511.10507

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨AffordBot: 3D Fine-grained Embodied Reasoning via Multimodal Large Language Models

📝 Summary:
AffordBot uses MLLMs and chain-of-thought reasoning for fine-grained 3D embodied reasoning. It predicts affordance elements' location, motion type, and axis in 3D scenes per instructions. It achieves state-of-the-art by projecting 3D elements for 2D MLLMs.

🔹 Publication Date: Published on Nov 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10017
• PDF: https://arxiv.org/pdf/2511.10017

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

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

#AffordBot #MLLM #EmbodiedAI #3DReasoning #Robotics

✨SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control

📝 Summary:
SliderEdit enables continuous, fine-grained control over image editing instructions by using low-rank adaptation matrices, improving edit controllability, visual consistency, and user steerability. AI...

🔹 Publication Date: Published on Nov 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09715
• PDF: https://arxiv.org/pdf/2511.09715

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents

📝 Summary:
ResearchRubrics is a benchmark for evaluating deep research agents, using expert rubrics to assess their factual grounding, reasoning, and clarity across diverse, complex tasks. AI-generated summary D...

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07685
• PDF: https://arxiv.org/pdf/2511.07685

✨ Datasets citing this paper:
• https://huggingface.co/datasets/ScaleAI/researchrubrics

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

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

#AI #DataScience #MachineLearning #HuggingFace #Research

✨PAN: A World Model for General, Interactable, and Long-Horizon World Simulation

📝 Summary:
PAN is a general interactable world model that predicts future states through high-quality action-conditioned video simulation. It uses a GLP architecture combining LLM-based latent dynamics with a video diffusion decoder for detailed long-term coherent results enabling reasoning and acting.

🔹 Publication Date: Published on Nov 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09057
• PDF: https://arxiv.org/pdf/2511.09057

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

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

#WorldModels #AI #Simulation #GenerativeAI #Robotics

✨Hail to the Thief: Exploring Attacks and Defenses in Decentralised GRPO

📝 Summary:
This study identifies and demonstrates adversarial attacks in decentralized GRPO for LLMs, achieving 100% success rates by injecting malicious tokens. It also proposes effective defense mechanisms that can stop these attacks completely.

🔹 Publication Date: Published on Nov 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09780
• PDF: https://arxiv.org/pdf/2511.09780

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

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

#LLMs #AdversarialAttacks #AISecurity #DecentralizedAI #GRPO