✨TabDSR: Decompose, Sanitize, and Reason for Complex Numerical Reasoning in Tabular Data

📝 Summary:
TabDSR improves LLM performance on complex tabular numerical reasoning by decomposing queries, sanitizing tables, and using program-of-thoughts reasoning. It achieves state-of-the-art accuracy, consistently outperforming existing methods.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02219
• PDF: https://arxiv.org/pdf/2511.02219

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#LLM #TabularData #NumericalReasoning #DataScience #AI

✨Don't Blind Your VLA: Aligning Visual Representations for OOD Generalization

📝 Summary:
Naive action fine-tuning degrades visual representations in Vision-Language-Action models. This study analyzes this degradation and introduces a simple method to align representations, improving out-of-distribution generalization.

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25616
• PDF: https://arxiv.org/pdf/2510.25616
• Project Page: https://blind-vla-paper.github.io
• Github: https://github.com/CognitiveAISystems/BlindVLA

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#VLA #OODGeneralization #ComputerVision #MachineLearning #RepresentationLearning

✨The Collaboration Gap

📝 Summary:
A new benchmark reveals a collaboration gap where AI models performing well solo degrade significantly when paired. Starting with a stronger agent relay inference helps bridge this gap. This suggests a need for collaboration-aware evaluation and training.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02687
• PDF: https://arxiv.org/pdf/2511.02687

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#AI #Collaboration #MultiAgentSystems #AIResearch #AIEvaluation

✨LightRAG: Simple and Fast Retrieval-Augmented Generation

📝 Summary:
LightRAG improves Retrieval-Augmented Generation by addressing limitations of flat data representations and inadequate contextual awareness. It integrates graph structures into text indexing and retrieval, enhancing accuracy, efficiency, and response times through a dual-level system.

🔹 Publication Date: Published on Oct 8, 2024

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2410.05779
• PDF: https://arxiv.org/pdf/2410.05779
• Github: https://github.com/hkuds/lightrag

✨ Spaces citing this paper:
• https://huggingface.co/spaces/rm-lht/lightrag

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#RAG #AI #NLP #GraphAI #InformationRetrieval

✨RiddleBench: A New Generative Reasoning Benchmark for LLMs

📝 Summary:
RiddleBench, a new benchmark of 1,737 puzzles, reveals fundamental weaknesses in state-of-the-art LLMs, including hallucination cascades and poor self-correction. Models achieve only about 60% accuracy, underscoring the need for more robust and reliable reasoning capabilities.

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24932
• PDF: https://arxiv.org/pdf/2510.24932

✨ Datasets citing this paper:
• https://huggingface.co/datasets/ai4bharat/RiddleBench

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#LLMs #GenerativeAI #AIResearch #Benchmarks #NLP

✨AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications

📝 Summary:
AgentScope 1.0 is a developer-centric framework for building agentic applications. It offers flexible tool-based interactions, unified interfaces, and ReAct-based infrastructure to enable efficient and safe development and deployment.

🔹 Publication Date: Published on Aug 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2508.16279
• PDF: https://arxiv.org/pdf/2508.16279
• Github: https://github.com/agentscope-ai/agentscope

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#AIAgents #AIdevelopment #SoftwareFramework #AItools #ReActAI

✨RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies

📝 Summary:
RoboChallenge is an online evaluation system for robotic control algorithms, especially VLA models. It enables large-scale, reproducible real-robot testing to survey state-of-the-art models.

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17950
• PDF: https://arxiv.org/pdf/2510.17950

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#Robotics #AI #MachineLearning #EmbodiedAI #RoboticsEvaluation

✨Reg-DPO: SFT-Regularized Direct Preference Optimization with GT-Pair for Improving Video Generation

📝 Summary:
This paper presents GT-Pair for automatic preference data construction and Reg-DPO, which adds SFT loss to DPO for stable training. Combined with memory optimizations, it significantly improves video generation quality, outperforming existing methods.

🔹 Publication Date: Published on Nov 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.01450
• PDF: https://arxiv.org/pdf/2511.01450
• Github: https://github.com/JieDuTQS/Reg-DPO

🔹 Models citing this paper:
• https://huggingface.co/dujielvtqs/Reg-DPO

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#VideoGeneration #GenerativeAI #DeepLearning #DPO #AIResearch

✨AyurParam: A State-of-the-Art Bilingual Language Model for Ayurveda

📝 Summary:
AyurParam-2.9B is a bilingual language model for Ayurveda, outperforming smaller models and competing with larger ones on medical tasks. Highlighting the need for domain adaptation and quality data.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02374
• PDF: https://arxiv.org/pdf/2511.02374

🔹 Models citing this paper:
• https://huggingface.co/bharatgenai/AyurParam

✨ Spaces citing this paper:
• https://huggingface.co/spaces/Swanand3/BharatGen_AyurParam

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#Ayurveda #LanguageModel #BilingualAI #NLP #HealthcareAI

✨3D Gaussian Splatting for Real-Time Radiance Field Rendering

📝 Summary:
This paper introduces a method using 3D Gaussians for scene representation to achieve state-of-the-art, high-quality real-time novel-view synthesis at 1080p resolution. It optimizes anisotropic Gaussians and uses a fast rendering algorithm, outperforming previous radiance field methods.

🔹 Publication Date: Published on Aug 8, 2023

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2308.04079
• PDF: https://arxiv.org/pdf/2308.04079
• Github: https://github.com/graphdeco-inria/gaussian-splatting

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Voxel51/gaussian_splatting

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#3DGaussianSplatting #RadianceFields #ComputerGraphics #RealTimeRendering #NovelViewSynthesis

🤖🧠 Krea Realtime 14B: Redefining Real-Time Video Generation with AI

🗓️ 05 Nov 2025
📚 AI News & Trends

The field of artificial intelligence is undergoing a remarkable transformation and one of the most exciting developments is the rise of real-time video generation. From cinematic visual effects to immersive virtual environments, AI is rapidly blurring the boundaries between imagination and reality. At the forefront of this innovation stands Krea Realtime 14B, an advanced open-source ...

#AI #RealTimeVideo #ArtificialIntelligence #OpenSource #VideoGeneration #KreaRealtime14B

✨DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion

📝 Summary:
DyPE enhances diffusion transformers for ultra-high-resolution image generation by dynamically adjusting positional encodings. This training-free method allows pre-trained models to synthesize images far beyond their training resolution, achieving state-of-the-art fidelity without extra sampling ...

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20766
• PDF: https://arxiv.org/pdf/2510.20766
• Project Page: https://noamissachar.github.io/DyPE/
• Github: https://github.com/guyyariv/DyPE

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#DiffusionModels #ImageGeneration #HighResolution #DeepLearning #ComputerVision

✨MME-CC: A Challenging Multi-Modal Evaluation Benchmark of Cognitive Capacity

📝 Summary:
MME-CC is a new vision-grounded benchmark to evaluate multimodal large language models cognitive capacity in spatial, geometric, and knowledge-based reasoning tasks. It reveals that while some models lead, spatial and geometric reasoning remain broadly weak. This highlights the need for better ev...

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03146
• PDF: https://arxiv.org/pdf/2511.03146
• Project Page: https://randomtutu.github.io/MME-CC/

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#MultimodalAI #LLMs #Benchmarking #CognitiveAI #ComputerVision

✨LEGO-Eval: Towards Fine-Grained Evaluation on Synthesizing 3D Embodied Environments with Tool Augmentation

📝 Summary:
The paper introduces LEGO-Eval, a tool-augmented framework, and LEGO-Bench, a detailed instruction benchmark, to improve 3D scene evaluation. It shows LEGO-Eval accurately assesses scene-instruction alignment, outperforming VLMs, and current generation methods largely fail to create realistic sce...

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03001
• PDF: https://arxiv.org/pdf/2511.03001
• Project Page: https://gyeomh.github.io/LEGO-Eval/

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#EmbodiedAI #3DGeneration #EvaluationMetrics #VLMs #Benchmarking

✨Let Multimodal Embedders Learn When to Augment Query via Adaptive Query Augmentation

📝 Summary:
M-Solomon is a multimodal embedder that adaptively decides when to augment queries. It uses a Multimodal LLM to generate augmentations for queries that require them, learning to augment only when necessary. This approach improves performance and significantly reduces embedding latency compared to...

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02358
• PDF: https://arxiv.org/pdf/2511.02358

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#MultimodalAI #LLM #Embeddings #MachineLearning #DeepLearning

✨LiveTradeBench: Seeking Real-World Alpha with Large Language Models

📝 Summary:
LiveTradeBench evaluates LLMs in live trading environments with real-time data, multi-asset portfolios, and multiple markets. It reveals that strong static benchmark scores dont predict trading success, and some LLMs can adapt to live market signals. This highlights a gap in current LLM evaluations.

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03628
• PDF: https://arxiv.org/pdf/2511.03628
• Project Page: https://trade-bench.live/
• Github: https://github.com/ulab-uiuc/live-trade-bench

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#LLM #AlgorithmicTrading #FinancialAI #QuantitativeFinance #AIResearch

✨Kinematify: Open-Vocabulary Synthesis of High-DoF Articulated Objects

📝 Summary:
Kinematify is an automated framework that synthesizes high-DoF articulated objects from images or text. It infers kinematic topologies and estimates joint parameters, combining MCTS search with geometry-driven optimization for physically consistent models.

🔹 Publication Date: Published on Nov 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.01294
• PDF: https://arxiv.org/pdf/2511.01294

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#3DModeling #ComputerVision #Robotics #AIResearch #Kinematics

✨Diffusion Language Models are Super Data Learners

📝 Summary:
Diffusion Language Models DLMs consistently outperform autoregressive models, especially in low-data settings. This is due to any-order modeling, iterative bidirectional denoising, and Monte Carlo augmentation. DLMs maintain advantages at scale, achieving strong performance even by repeating limi...

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03276
• PDF: https://arxiv.org/pdf/2511.03276
• Project Page: https://github.com/JinjieNi/dlms-are-super-data-learners
• Github: https://github.com/JinjieNi/OpenMoE2

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#DiffusionModels #LanguageModels #MachineLearning #LowDataLearning #AI

✨Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning

📝 Summary:
Orion-MSP is a novel tabular in-context learning architecture addressing limitations in existing models. It incorporates multi-scale processing, block-sparse attention, and a Perceiver-style memory. Orion-MSP achieves state-of-the-art performance on various benchmarks while scaling effectively to...

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02818
• PDF: https://arxiv.org/pdf/2511.02818

🔹 Models citing this paper:
• https://huggingface.co/Lexsi/Orion-MSP

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#TabularLearning #SparseAttention #MachineLearning #DeepLearning #AI

✨TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models

📝 Summary:
TabTune is a unified library that standardizes the workflow for tabular foundation models. It provides consistent access to state-of-the-art models, diverse adaptation strategies, and integrated evaluation for performance, calibration, and fairness.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02802
• PDF: https://arxiv.org/pdf/2511.02802
• Github: https://github.com/Lexsi-Labs/TabTune

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#TabularData #FoundationModels #MachineLearning #DataScience #AIResearch

✨UniAVGen: Unified Audio and Video Generation with Asymmetric Cross-Modal Interactions

📝 Summary:
UniAVGen uses dual Diffusion Transformers and Asymmetric Cross-Modal Interaction for unified audio-video generation. This framework ensures precise spatiotemporal synchronization and semantic consistency. It outperforms existing methods in sync and consistency with far fewer training samples.

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03334
• PDF: https://arxiv.org/pdf/2511.03334
• Project Page: https://mcg-nju.github.io/UniAVGen/
• Github: https://mcg-nju.github.io/UniAVGen/

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

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

#GenerativeAI #AudioVideoGeneration #DiffusionModels #CrossModalAI #DeepLearning