LLM vs RAG vs Agent by hand ✍️ Workbook

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🤖🧠 DeepAgent: A New Era of General AI Reasoning and Scalable Tool-Use Intelligence

🗓️ 09 Nov 2025
📚 AI News & Trends

Artificial intelligence has rapidly progressed from simple assistants to advanced reasoning systems capable of complex problem-solving. As tasks demand more autonomy, adaptability and real-world interaction, the AI field has entered the era of intelligent agent systems. These agents are expected not just to answer questions, but to think, plan, search, act and interact across digital ...

#GeneralAI #ArtificialIntelligence #AIReasoning #IntelligentAgents #ScalableAI #ToolUseAI

✨Part II: ROLL Flash -- Accelerating RLVR and Agentic Training with Asynchrony

📝 Summary:
ROLL Flash enhances LLM RL post-training using asynchronous methods. It employs fine-grained parallelism and rollout-train decoupling to boost resource use and scalability. This achieves up to 2.72x speedup while matching synchronous training performance.

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11345
• PDF: https://arxiv.org/pdf/2510.11345
• Github: https://github.com/alibaba/ROLL

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#LLM #ReinforcementLearning #AsynchronousAI #DeepLearning #AIResearch

🤖🧠 PokeeResearch: Advancing Deep Research with AI and Web-Integrated Intelligence

🗓️ 09 Nov 2025
📚 AI News & Trends

In the modern information era, the ability to research fast, accurately and at scale has become a competitive advantage for businesses, researchers, analysts and developers. As online data expands exponentially, traditional search engines and manual research workflows are no longer sufficient to gather reliable insights efficiently. This need has fueled the rise of AI research ...

#AIResearch #DeepResearch #WebIntelligence #ArtificialIntelligence #ResearchAutomation #DataAnalysis

🤖🧠 Pico-Banana-400K: The Breakthrough Dataset Advancing Text-Guided Image Editing

🗓️ 09 Nov 2025
📚 AI News & Trends

Text-guided image editing has rapidly evolved with powerful multimodal models capable of transforming images using simple natural-language instructions. These models can change object colors, modify lighting, add accessories, adjust backgrounds or even convert real photographs into artistic styles. However, the progress of research has been limited by one crucial bottleneck: the lack of large-scale, high-quality, ...

#TextGuidedEditing #MultimodalAI #ImageEditing #AIResearch #ComputerVision #DeepLearning

✨Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library

📝 Summary:
ROLL is an efficient, scalable, and user-friendly library for large-scale reinforcement learning optimization. It features a simplified architecture, parallel training, flexible sample management, and resource mapping for developers and researchers.

🔹 Publication Date: Published on Jun 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.06122
• PDF: https://arxiv.org/pdf/2506.06122
• Github: https://github.com/alibaba/roll

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#ReinforcementLearning #MachineLearning #LargeScaleAI #Optimization #AIResearch

🤖🧠 Concerto: How Joint 2D-3D Self-Supervised Learning Is Redefining Spatial Intelligence

🗓️ 09 Nov 2025
📚 AI News & Trends

The world of artificial intelligence is rapidly evolving and self-supervised learning has become a driving force behind breakthroughs in computer vision and 3D scene understanding. Traditional supervised learning relies heavily on labeled datasets which are expensive and time-consuming to produce. Self-supervised learning, on the other hand, extracts meaningful patterns without manual labels allowing models to ...

#SelfSupervisedLearning #ComputerVision #3DSceneUnderstanding #SpatialIntelligence #AIResearch #DeepLearning

✨CritiCal: Can Critique Help LLM Uncertainty or Confidence Calibration?

📝 Summary:
CritiCal, a novel training method using natural language critiques, significantly improves LLM confidence calibration. This method outperforms other approaches, including GPT-4o, enhancing reliability and generalization across tasks.

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24505
• PDF: https://arxiv.org/pdf/2510.24505

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#LLM #ConfidenceCalibration #MachineLearning #NLP #AIResearch

✨HAFixAgent: History-Aware Automated Program Repair Agent

📝 Summary:
HAFixAgent enhances automated program repair for complex multi-hunk bugs by incorporating repository history. It significantly improves bug-fixing effectiveness over existing agent-based systems while maintaining efficiency. This offers a practical approach for history-aware agentic APR.

🔹 Publication Date: Published on Nov 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.01047
• PDF: https://arxiv.org/pdf/2511.01047

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#AutomatedProgramRepair #SoftwareEngineering #AI #BugFixing #CodeRepair

✨VeriCoT: Neuro-symbolic Chain-of-Thought Validation via Logical Consistency Checks

📝 Summary:
VeriCoT is a neuro-symbolic method to validate LLM Chain-of-Thought reasoning. It formalizes CoT steps into first-order logic for automated verification of consistency. This improves LLM reliability by identifying flawed reasoning and enhancing overall accuracy.

🔹 Publication Date: Published on Nov 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2511.04662
• PDF: https://arxiv.org/pdf/2511.04662

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#LLM #ChainOfThought #NeuroSymbolic #AI #Logic

✨VGGT: Visual Geometry Grounded Transformer

📝 Summary:
VGGT is a novel feed-forward neural network that efficiently infers multiple key 3D scene attributes from single or multiple views. It outperforms existing specialized models without requiring post-processing, achieving state-of-the-art results across several 3D computer vision tasks. VGGT also s...

🔹 Publication Date: Published on Mar 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2503.11651
• PDF: https://arxiv.org/pdf/2503.11651
• Project Page: https://vgg-t.github.io/
• Github: https://github.com/facebookresearch/vggt

🔹 Models citing this paper:
• https://huggingface.co/facebook/VGGT-1B
• https://huggingface.co/facebook/VGGT-1B-Commercial

✨ Spaces citing this paper:
• https://huggingface.co/spaces/facebook/vggt
• https://huggingface.co/spaces/Pointcept/Concerto
• https://huggingface.co/spaces/HanzhouLiu/Stylos_Demo

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#3DComputerVision #Transformers #DeepLearning #ComputerVision #AI

✨Real-Time Reasoning Agents in Evolving Environments

📝 Summary:
AI agents struggle with real-time reasoning in dynamic environments, failing to balance logical judgments with timely responses. This paper introduces Real-Time Reasoning Gym and AgileThinker. AgileThinker combines reactive and planning approaches to effectively balance reasoning depth and respon...

🔹 Publication Date: Published on Nov 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.04898
• PDF: https://arxiv.org/pdf/2511.04898
• Project Page: https://realtimegym.saltlab.stanford.edu
• Github: https://github.com/SALT-NLP/RealtimeGym

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#AI #RealTimeAI #AutonomousAgents #DynamicEnvironments #MachineLearning

✨HaluMem: Evaluating Hallucinations in Memory Systems of Agents

📝 Summary:
HaluMem is a new benchmark that evaluates memory hallucinations in AI systems by localizing them to specific stages: extraction, updating, and question answering. It uses large human-AI interaction datasets. Findings show current systems accumulate hallucinations during extraction and updating, w...

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03506
• PDF: https://arxiv.org/pdf/2511.03506
• Github: https://github.com/MemTensor/HaluMem

✨ Datasets citing this paper:
• https://huggingface.co/datasets/IAAR-Shanghai/HaluMem

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#AIHallucinations #AIAgents #MemorySystems #LLM #AIResearch

✨RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Services

📝 Summary:
RedOne 2.0 is an SNS-oriented LLM trained with a progressive, RL-prioritized post-training paradigm for rapid and stable adaptation to social networking challenges. This 4B model significantly improves over a 7B baseline and achieves an 8.74 performance lift from base models with less data, demon...

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07070
• PDF: https://arxiv.org/pdf/2511.07070

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#LLM #SocialNetworking #ReinforcementLearning #NLP #DeepLearning

✨RLoop: An Self-Improving Framework for Reinforcement Learning with Iterative Policy Initialization

📝 Summary:
RLoop is a self-improving framework addressing Reinforcement Learning overfitting and generalization issues. It uses iterative policy initialization and Rejection-sampling Fine-Tuning to convert diverse policy variations into robust performance gains, boosting accuracy and mitigating catastrophic...

🔹 Publication Date: Published on Nov 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.04285
• PDF: https://arxiv.org/pdf/2511.04285

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#ReinforcementLearning #MachineLearning #AI #DeepLearning #Generalization

✨Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs

📝 Summary:
MoE LLMs have suboptimal routers that cause significant performance gaps. Routing Manifold Alignment RoMA aligns routing weights with task embeddings using a regularization term during lightweight finetuning of routers. This improves generalization by encouraging similar samples to share expert c...

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07419
• PDF: https://arxiv.org/pdf/2511.07419
• Github: https://github.com/tianyi-lab/RoMA

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#LLMs #MixtureOfExperts #DeepLearning #AI #MachineLearning

✨DIMO: Diverse 3D Motion Generation for Arbitrary Objects

📝 Summary:
DIMO is a generative AI that creates diverse 3D motions for any object from one image. It extracts motion patterns from video models into a latent space, using neural key point trajectories to drive 3D object models. This enables sampling diverse motions and applications like interpolation.

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07409
• PDF: https://arxiv.org/pdf/2511.07409

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#DIMO #3DMotion #GenerativeAI #ComputerVision #DeepLearning

✨IterResearch: Rethinking Long-Horizon Agents via Markovian State Reconstruction

📝 Summary:
IterResearch improves long-horizon reasoning by reformulating it as a Markov Decision Process with strategic workspace reconstruction. This novel paradigm overcomes context suffocation, achieving substantial performance gains and unprecedented interaction scaling, and also serves as an effective ...

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07327
• PDF: https://arxiv.org/pdf/2511.07327

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#ReinforcementLearning #AI #MachineLearning #AIagents #MDP

✨MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal LLMs

📝 Summary:
MVU-Eval is a new comprehensive benchmark for evaluating Multi-Video Understanding in Multimodal Large Language Models. It addresses a critical gap in existing single-video benchmarks and reveals significant performance limitations in current MLLMs for multi-video scenarios.

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07250
• PDF: https://arxiv.org/pdf/2511.07250
• Project Page: https://huggingface.co/datasets/MVU-Eval-Team/MVU-Eval-Data
• Github: https://github.com/NJU-LINK/MVU-Eval

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#MLLMs #VideoUnderstanding #AI #Benchmarking #ComputerVision

✨The Station: An Open-World Environment for AI-Driven Discovery

📝 Summary:
The Station is an open-world multi-agent AI environment enabling autonomous scientific discovery. Agents engage in full scientific journeys, achieving state-of-the-art results across diverse benchmarks. This new paradigm fosters emergent behaviors and novel method development, moving beyond rigid...

🔹 Publication Date: Published on Nov 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.06309
• PDF: https://arxiv.org/pdf/2511.06309
• Github: https://github.com/dualverse-ai/station

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#AI #MultiAgentSystems #ScientificDiscovery #OpenWorldAI #AutonomousAI