“The bot uses RAG (Retrieval-Augmented Generation) to answer based on search results.”

“The article's focus on OpenAI's Realtime API highlights its potential for creating responsive, engaging conversational AI.”

“By structuring the system around retrieval, answer synthesis, and self-evaluation, we demonstrate how agentic patterns […]”

“Apple selects Google’s Gemini for Siri.”

“RAG is a mechanism that 'searches external knowledge (documents) and passes that information to the LLM to generate answers.'”

“This article explains the basic mechanisms of RAG using sample code.”

“By guiding LLMs with case-augmented reasoning instead of extensive code-like safety rules, we avoid rigid adherence to narrowly enumerated rules and enable broader adaptability.”

“The article is a summary and technical extract from a blog post at https://agenticai-flow.com/posts/agentic-rag-advanced-retrieval/”

“…AI assistants should automatically search for relevant manuals and answer questions...”

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“RAG（Retrieval-Augmented Generation）は、大規模言語モデルに外部知識を与えて回答精度を高める技術です。”

“"画像がダメなら、テキストだ」ということで、今回はDifyのナレッジ（RAG）機能を使い、ローカルのRAG環境を構築します。”

“To address these limitations, we propose HyperJoin, a large language model (LLM)-augmented Hypergraph framework for Joinable table discovery.”

“Exploratory results demonstrated that ConvNeXt-Tiny achieved the highest performance, attaining a 96.88% accuracy on the test”

“In this tutorial, we build an advanced yet practical multi-agent system using OpenAI Swarm that runs in Colab. We demonstrate how we can orchestrate specialized agents, such as a triage agent, an SRE agent, a communications agent, and a critic, to collaboratively handle a real-world production incident scenario.”

“"I was tired of the RAG implementation with ChatGPT, so I completely switched to Gemini Pro's 'brute-force long context'."”

“"RAG (Retrieval-Augmented Generation) is a representative mechanism for solving these problems."”

“AdaGReS introduces a closed-form, instance-adaptive calibration of the relevance-redundancy trade-off parameter to eliminate manual tuning and adapt to candidate-pool statistics and budget limits.”

“DLMs augmented with polynomial-length chain-of-thought (CoT) can simulate any parallel sampling algorithm using an optimal number of sequential steps.”

“RAG assistants leak secrets in up to 26.56% of interactions.”

“R-Debater achieves higher single-turn and multi-turn scores compared with strong LLM baselines, and human evaluation confirms its consistency and evidence use.”

“The resulting formulation is based on a 4D Hodge-Laplacian operator with a spatiotemporal diffusion tensor and convection field, augmented by a small temporal perturbation to ensure nondegeneracy.”

“The framework delivers a 3x increase in task processing speed over single-agent baselines, 98.7% structural/style consistency in writing, and a 74.6% test pass rate in coding.”

“The paper claims "significant superiority" and "faster convergence, enhanced training stability, and improved robustness to noise interference" compared to conventional optimization algorithms.”

“The paper introduces a Physics-Aware Groupwise Direct Preference Optimization (PhyGDPO) framework that builds upon the groupwise Plackett-Luce probabilistic model to capture holistic preferences beyond pairwise comparisons.”

“The results showcase the real-world feasibility and superior performance of nonlinear MPC for 3D path-following guidance at ground speeds up to 36 meters per second.”

“The paper states that RAGPart and RAGMask consistently reduce attack success rates while preserving utility under benign conditions.”

“RAG enhances the way AI systems process and generate information. By pulling from external data, it offers more contextually relevant outputs.”

“SPARK formalizes a persona space defined by role, expertise, task context, and domain, and introduces a Persona Coordinator that dynamically interprets incoming queries to activate the most relevant specialized agents.”

“LoZA can achieve significant speed-ups both for prefill-intensive (e.g., retrieval-augmented generation) and decode-intensive (e.g., tool-integrated reasoning) cases.”

“HGMem extends the concept of memory beyond simple storage into a dynamic, expressive structure for complex reasoning and global understanding.”

“The paper establishes asymptotically tight lower and upper bounds on the over-thresholds and shows that for infinitely many instances of m the two bounds coincide.”

“The resulting augmented excess free-energy functional quantitatively reproduces equilibrium density profiles, coexistence curves, and surface tensions across a broad temperature range, and accurately predicts contact angles and droplet shapes far beyond the training regime.”

“The LLM often generates incorrect answers instead of declining to respond, which constitutes a major source of error.”

“XGBoost reaches 99.59% accuracy with microsecond-level inference using an augmented and LLM-filtered dataset.”

“AI that answers while looking at your own reference books, instead of only talking from its own memory.”

“RobustMask successfully certifies over 20% of candidate documents within the top-10 ranking positions against adversarial perturbations affecting up to 30% of their content.”

““We demonstrate that a surgical VLA policy trained with these augmented data significantly outperforms models trained only on real demonstrations on a real surgical robot platform.””

“The article mentions the use of pdfplumber, tesseract, and Gemini 3 Flash for PDF processing and Markdown conversion.”

“Even advanced search-augmented models like GPT-5.1 (w/ Search) achieve only 15.24% accuracy.”

“"I am working on a financial analysis rag bot it is like user can upload a financial report and on that they can ask any question regarding to that . I am facing issues so if anyone has worked on same problem or has came across a repo like this kindly DM pls help we can make this project together"”

“The author wants to automatically evaluate whether search results provide the basis for answering questions using an LLM.”

“FasterPy combines Retrieval-Augmented Generation (RAG), supported by a knowledge base constructed from existing performance-improving code pairs and corresponding performance measurements, with Low-Rank Adaptation (LoRA) to enhance code optimization performance.”

“I need help learning how to create a RAG system, do you guys have any recommendations on which material to learn from, it would really help me figuring out stuff.”

“The framework identifies reflection as the key mechanism that enables agents to adapt through interaction without back propagation or model fine tuning.”

“TravelBench offers a practical and reproducible benchmark for advancing LLM agents in travel planning.”

“DICE achieves 85.7% agreement with human experts, substantially outperforming existing LLM-based metrics such as RAGAS.”

“The paper proposes that to achieve safe, interpretable, energy-efficient, and human-like AI, foundation models should integrate actions, at multiple scales of abstraction, with a compositional generative architecture and episodic memory.”

“HiFi-RAG outperforms the parametric baseline by 57.4% in ROUGE-L and 14.9% in DeBERTaScore on Test2025.”