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  • All entries123,104
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123,104Total entries
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Knowledge catalogue

Search: “rag”

GridTimelineEvolution
49+ results
Research

RAG-Stack: Co-Optimizing RAG Serving Performance and Quality

DGX agent

arXiv:2608.03487v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG), which augments large language model (LLM) generation with information retrieved from databases, has become a wid

researcharxiv-cs-ai
6 Aug 2026
Model Releases
DGX agent

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RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems

DGX agent

arXiv:2610.08571v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to prompt-injection attacks embedded in retrieved content. We introduce RAG-PIBench, a ben

model-releasesarxiv-cs-ai
7 Oct 2026
Agents

Is Agentic RAG worth it? An experimental comparison of RAG approaches

DGX agent

arXiv:2601.07711v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are usually defined by the combination of a generator and a retrieval component that extracts textual c

agentsarxiv-cs-cl
21 Apr 2026
Model Releases

post-graph-rag: A PostgreSQL-Native Bi-Temporal Graph RAG Engine with Temporal Grounding at Synthesis

DGX agent

arXiv:2608.24921v2 Announce Type: replace Abstract: Graph RAG connects facts no single passage states, but implementations pay three times: in infrastructure, keeping vector store, graph database and

model-releasesarxiv-cs-ai
1 Sept 2026
Model Releases

CMT-RAG: Complementary Memory Traces for Multi-turn Multi-hop RAG

DGX agent

arXiv:2607.26470v1 Announce Type: new Abstract: Multi-turn information-seeking conversations require both multi-hop reasoning and long-range dependency tracking across turns. However, existing RAG sys

model-releasesarxiv-cs-cl
30 Jul 2026
Research

Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG

DGX agent

arXiv:2509.14435v3 Announce Type: replace Abstract: Large language models (LLMs) have transformed natural language processing (NLP), enabling diverse applications by integrating large-scale pre-traine

researcharxiv-cs-cl
4 Sept 2026
Model Releases

Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAG

DGX agent

arXiv:2609.03749v1 Announce Type: cross Abstract: Third-party retrieval-augmented generation (RAG) marketplaces create a new auditing problem: data providers may license corpora to a RAG operator, yet

model-releasesarxiv-cs-cl
4 Sept 2026
Local Ai

HAM-RAG: Hierarchy-Aware Multimodal RAG for Structure-Faithful Interleaved Generation

DGX agent

arXiv:2608.14032v1 Announce Type: cross Abstract: Existing multimodal RAG methods often flatten structured documents into isolated text and image units, weakening the source organization and local tex

local-aiarxiv-cs-ai
17 Aug 2026
Research

PACE-RAG: Patient-Aware Contextual and Evidence-Constrained RAG for Clinical Drug Recommendation

DGX agent

arXiv:2603.17356v3 Announce Type: replace Abstract: Drug recommendation requires a deep understanding of individual patient context, especially for complex conditions like Parkinson's disease. While L

researcharxiv-cs-cl
1 Sept 2026
Model Releases

NeSy-RAG: Neuro-Symbolic RAG for Explainable Question Answering

DGX agent

arXiv:2608.06292v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves question answering by grounding large language models (LLMs) in external knowledge such as text corpora. H

model-releasesarxiv-cs-cl
7 Aug 2026
Research

H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations

DGX agent

arXiv:2605.00631v1 Announce Type: new Abstract: We present H-RAG, our submission to SemEval-2026 Task 8 (MTRAGEval), addressing both Task A (Retrieval) and Task C (Generation with Retrieved Passages).

researcharxiv-cs-cl
4 May 2026
Applications

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation

DGX agent

arXiv:2604.16310v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems using static multi-turn datasets fails to capture the dynamic nature of real-world dialogues.

applicationsarxiv-cs-cl
21 Apr 2026
Model Releases

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

DGX agent

arXiv:2604.04036v2 Announce Type: replace-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challengin

model-releasesarxiv-cs-cl
11 Sept 2026
Research

PAGE-RAG: Provenance-Aware Graph Evidence Promotion for Fixed-Budget Multi-hop Retrieval-Augmented Generation

DGX agent

arXiv:2608.29753v1 Announce Type: new Abstract: Multi-hop question answering in retrieval-augmented gener?ation (RAG) often benefits from retrieving beyond the few candidates that will finally be read

researcharxiv-cs-ai
1 Sept 2026
Safety

GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering

DGX agent

arXiv:2608.22634v1 Announce Type: cross Abstract: Current work on improving reliability in large language model (LLM)- generated answers has primarily leveraged Retrieval-Augmented Generation (RAG), k

safetyarxiv-cs-ai
25 Aug 2026
Model Releases

LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking

DGX agent

arXiv:2506.07449v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have driven their adoption in recommender systems through Retrieval-Augmented Generation (RAG)

model-releasesarxiv-cs-ai
18 Aug 2026
Applications

Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

DGX agent

arXiv:2604.12185v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including

applicationsarxiv-cs-cl
15 Apr 2026
Research

HKVM-RAG: Key-Value-Separated Hypergraph Evidence Organization for Multi-Hop RAG

DGX agent

arXiv:2606.07218v1 Announce Type: cross Abstract: Multi-hop RAG poses a data-engineering problem beyond passage matching: under fixed retrieval budgets, a system must organize retrieved text into evid

researcharxiv-cs-cl
8 Jun 2026
Model Releases

Domain-oriented RAG Assessment (DoRA): Synthetic Benchmarking for RAG-based Question Answering on Defense Documents

DGX agent

arXiv:2604.17943v1 Announce Type: new Abstract: Open-domain RAG benchmarks over public corpora can overestimate deployment performance due to pretraining overlap and weak attribution requirements. We

model-releasesarxiv-cs-cl
21 Apr 2026
Model Releases

Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model Family

DGX agent

arXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained

model-releasesarxiv-cs-cl
7 Oct 2026
Model Releases

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models

DGX agent

arXiv:2606.04739v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generatio

model-releasesarxiv-cs-ai
4 Jun 2026
Research

R^{2}Adapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG

DGX agent

arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla

researcharxiv-cs-cl
4 Sept 2026
Research

Next-Gen Sponsored Search: Crafting the Perfect Query with Inventory-Aware RAG (InvAwr-RAG) Based GenAI

DGX agent

arXiv:2607.03880v1 Announce Type: cross Abstract: Sponsored search plays a crucial role in e-commerce revenue generation, where advertisers strategically bid on keywords to capture the attention of us

researcharxiv-cs-ai
7 Jul 2026
Agents

Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization

DGX agent

arXiv:2606.25656v1 Announce Type: new Abstract: As advanced RAG variants like GraphRAG and Agentic RAG emerge, one leading question is when and how to use them. Here, we introduce a framework for diff

agentsarxiv-cs-cl
25 Jun 2026
Research

Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains

DGX agent

arXiv:2505.16014v5 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems deployed in sensitive domains must provide interpretable evidence selection and robust safeguards again

researcharxiv-cs-cl
3 Jun 2026
Model Releases

MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG

DGX agent

arXiv:2604.24564v1 Announce Type: new Abstract: Multimodal Retrieval-Augmented Generation (MRAG) addresses key limitations of Multimodal Large Language Models (MLLMs), such as hallucination and outdat

model-releasesarxiv-cs-cl
28 Apr 2026
Agents

Personalizing Student-Agent Interactions Using Log-Contextualized Retrieval-Augmented Generation (RAG)

DGX agent

arXiv:2505.17238v3 Announce Type: replace Abstract: Collaborative dialogue offers rich insights into students' learning and critical thinking, which is essential for personalizing pedagogical agent in

agentsarxiv-cs-cl
21 Apr 2026
Research

ISO-RAG: Isoperimetric Noise Control for Retrieval-Augmented Generation

DGX agent

arXiv:2609.00513v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates large language models (LLMs) hallucinations, yet conventional dense retrieval struggles with the complex

researcharxiv-cs-ai
2 Sept 2026
Research

AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMS

DGX agent

arXiv:2608.09214v1 Announce Type: cross Abstract: Recent Retrieval-Augmented Generation (RAG) systems increasingly combine vector retrieval with structured knowledge, such as Graph RAG and Filtered ve

researcharxiv-cs-ai
11 Aug 2026
Safety

TA-RAG: Tone Awareness as a Design Imperative for Retrieval-Augmented Generation

DGX agent

arXiv:2608.06672v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a robust architecture for grounding large language models (LLMs) in trusted knowledge. However, standard

safetyarxiv-cs-cl
10 Aug 2026
Model Releases

RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM Safety

DGX agent

arXiv:2609.11758v1 Announce Type: new Abstract: Allowing large language models (LLMs) to retrieve information from a set of trusted documents can increase reliability and reduce hallucination. However

model-releasesarxiv-cs-cl
11 Sept 2026
Research

CoinRAG: Contextualized Information Nugget KV Cache Reuse for Long-Context RAG

DGX agent

arXiv:2608.07458v1 Announce Type: cross Abstract: Recent optimization studies on Retrieval-Augmented Generation (RAG) have exploited chunk-level KV cache reuse to avoid processing long retrieved conte

researcharxiv-cs-ai
10 Aug 2026
Model Releases

MKG-RAG-Bench: Benchmarking Retrieval in Multimodal Knowledge Graph-Augmented Generation

DGX agent

arXiv:2606.26458v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over knowledge graphs has emerged as a promising approach for grounding large language models, yet existing benchma

model-releasesarxiv-cs-ai
26 Jun 2026
Model Releases

IA-RAG: Interval-Algebra-Driven Temporal Reasoning for Dynamic Knowledge Retrieval

DGX agent

arXiv:2606.06044v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has shown strong effectiveness in grounding Large Language Models (LLMs) with external knowledge. However, existing

model-releasesarxiv-cs-cl
5 Jun 2026
Local Ai

FD-RAG: Federated Dual-System Retrieval-Augmented Generation

DGX agent

arXiv:2605.27432v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has emerged as a paradigm for grounding large language models in external knowledge, yet most existing RAG system

local-aiarxiv-cs-ai
28 May 2026
Safety

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation

DGX agent

arXiv:2601.02993v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a key paradigm for reducing factual hallucinations in Large Language Models (LLMs), yet little is kn

safetyarxiv-cs-cl
22 Apr 2026
Agents

MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation

DGX agent

arXiv:2604.18509v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in retrieval-augmented generation (RAG) to incorporate external knowledge at inference time. However, when

agentsarxiv-cs-cl
21 Apr 2026
Agents

M^3KG-RAG: Multi-hop Multimodal Knowledge Graph-enhanced Retrieval-Augmented Generation

DGX agent

arXiv:2512.20136v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has recently been extended to multimodal settings, connecting multimodal large language models (MLLMs) wi

agentsarxiv-cs-ai
14 Apr 2026
Model Releases

RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees

DGX agent

arXiv:2610.11370v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) grounds language models in external corpora. Agentic RAG enables iterative search, yet exposes the model to isolate

model-releasesarxiv-cs-ai
9 Oct 2026
Safety

CiteGuard-RAG: A Validation-Centered AI System for Evidence-Grounded Question Answering

DGX agent

arXiv:2609.15830v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) can improve access to complex information; however, retrieving evidence alone does not ensure that answers are gr

safetyarxiv-cs-ai
15 Sept 2026
Model Releases

When RAG Fails to Equalize: Geo-bias in Factual Question Answering over Public Companies

DGX agent

arXiv:2608.25717v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is widely assumed to mitigate factual errors in large language models (LLMs), but it remains unclear whether retrie

model-releasesarxiv-cs-cl
27 Aug 2026
Agents

Which RAG Paradigm Wins at Scale? A Scaling Study of Retrieval-Augmented Generation Paradigms

DGX agent

arXiv:2607.26497v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) methods range from lexical and dense retrieval to graph-based indexing and agentic search. They are usually evaluat

agentsarxiv-cs-cl
30 Jul 2026
Safety

When Should Active RAG Retrieve? A Budget-Aware Evaluation of Utility, Calibration, and Cost

DGX agent

arXiv:2607.24010v1 Announce Type: new Abstract: Active RAG systems decide when to retrieve external knowledge during generation, making them a budget-sensitive case of agentic RAG and self-adaptive re

safetyarxiv-cs-lg
28 Jul 2026
Research

In-depth Analysis of Graph-based RAG in a Unified Framework

DGX agent

arXiv:2503.04338v2 Announce Type: replace-cross Abstract: Graph-based Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs), imp

researcharxiv-cs-cl
28 Apr 2026
Research

Can QPP Choose the Right Query Variant? Evaluating Query Variant Selection for RAG Pipelines

DGX agent

arXiv:2604.22661v1 Announce Type: cross Abstract: Large Language Models (LLMs) have made query reformulation ubiquitous in modern retrieval and Retrieval-Augmented Generation (RAG) pipelines, enabling

researcharxiv-cs-cl
27 Apr 2026
Agents

HaS: Accelerating RAG through Homology-Aware Speculative Retrieval

DGX agent

arXiv:2604.20452v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as c

agentsarxiv-cs-cl
23 Apr 2026
Model Releases

Why RAGs Hallucinate: Penalty-Aware Evaluation of Retrieval-Augmented Generation Systems with Knowledge-Gap Canaries

DGX agent

arXiv:2608.26385v1 Announce Type: cross Abstract: Volume-based accuracy rewards retrieval-augmented generation (RAG) systems for guessing: a system that answers everything outscores one that declines

model-releasesarxiv-cs-ai
28 Aug 2026
Safety

The RAT: A Unified Bayesian Model for RAG Evaluation

DGX agent

arXiv:2608.24753v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems requires assessing not only end-to-end correctness but also how individual components interact

safetyarxiv-cs-ai
26 Aug 2026
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