RAG

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 758 papers with code (2,111 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
  22 May 2020 18 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  Large pre-trained language models have been shown to store factual knowledge in their parameters, and achieve state-of-the-art results when fine-tuned on downstream NLP tasks.
• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
  17 Oct 2023 6 repositories listed Syntology ran 8 of 14 samples · 6 unverified · 3 pointer-only (licence)
  Our framework trains a single arbitrary LM that adaptively retrieves passages on-demand, and generates and reflects on retrieved passages and its own generations using special tokens, called reflection tokens.
• R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
  7 Mar 2025 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  To address this, we propose \textbf{R1-Searcher}, a novel two-stage outcome-based RL approach designed to enhance the search capabilities of LLMs.
• ColPali: Efficient Document Retrieval with Vision Language Models
  27 Jun 2024 5 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  Documents are visually rich structures that convey information through text, but also figures, page layouts, tables, or even fonts.
• Retrieval-Augmented Generation for Large Language Models: A Survey
  18 Dec 2023 4 repositories listed
  Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.
• SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis
  22 May 2025 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Retrieval-augmented generation (RAG) systems have advanced large language models (LLMs) in complex deep search scenarios requiring multi-step reasoning and iterative information retrieval.
• R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning
  22 May 2025 3 repositories listed Syntology ran 1 of 10 samples · 9 unverified
  In this paper, we introduce R1-Searcher++, a novel framework designed to train LLMs to adaptively leverage both internal and external knowledge sources.
• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
  12 Mar 2025 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  Efficiently acquiring external knowledge and up-to-date information is essential for effective reasoning and text generation in large language models (LLMs).
• LRP4RAG: Detecting Hallucinations in Retrieval-Augmented Generation via Layer-wise Relevance Propagation
  28 Aug 2024 3 repositories listed
  Specifically, we first utilize LRP to compute the relevance between the input and output of the RAG generator.
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
  24 Apr 2024 3 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  To combine the strengths of these contrasting methods, we propose a Graph RAG approach to question answering over private text corpora that scales with both the generality of user questions and the quantity of source…
• Retrieval-Augmented Generation for AI-Generated Content: A Survey
  29 Feb 2024 3 repositories listed
  We first classify RAG foundations according to how the retriever augments the generator, distilling the fundamental abstractions of the augmentation methodologies for various retrievers and generators.
• The Power of Noise: Redefining Retrieval for RAG Systems
  26 Jan 2024 3 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  Retrieval-Augmented Generation (RAG) has recently emerged as a method to extend beyond the pre-trained knowledge of Large Language Models by augmenting the original prompt with relevant passages or documents retrieved…
• RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models
  31 Dec 2023 3 repositories listed Syntology ran 3 of 5 samples · 2 unverified
  Retrieval-augmented generation (RAG) has become a main technique for alleviating hallucinations in large language models (LLMs).
• RAGAS: Automated Evaluation of Retrieval Augmented Generation
  26 Sep 2023 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  We introduce RAGAs (Retrieval Augmented Generation Assessment), a framework for reference-free evaluation of Retrieval Augmented Generation (RAG) pipelines.
• Robust affine point matching via quadratic assignment on Grassmannians
  5 Mar 2023 3 repositories listed
  Robust Affine Matching with Grassmannians (RoAM) is a new algorithm to perform affine registration of point clouds.
• Arctic Long Sequence Training: Scalable And Efficient Training For Multi-Million Token Sequences
  16 Jun 2025 2 repositories listed
  ALST supports training Meta's Llama 8B model with 500K sequence length on a single H100 GPU, 3.
• A Survey of LLM × DATA
  24 May 2025 2 repositories listed
  The integration of large language model (LLM) and data management (DATA) is rapidly redefining both domains.
• Relevance Isn't All You Need: Scaling RAG Systems With Inference-Time Compute Via Multi-Criteria Reranking
  14 Mar 2025 2 repositories listed
  In response, we show evaluations of existing RAG methods which account for both context relevance and answer quality.
• Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts
  24 Feb 2025 2 repositories listed
  This paper introduces Multi-Modal Retrieval-Augmented Generation (M^2RAG), a benchmark designed to evaluate the effectiveness of Multi-modal Large Language Models (MLLMs) in leveraging knowledge from multi-modal…
• LettuceDetect: A Hallucination Detection Framework for RAG Applications
  24 Feb 2025 2 repositories listed
  Retrieval Augmented Generation (RAG) systems remain vulnerable to hallucinated answers despite incorporating external knowledge sources.
• Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
  18 Feb 2025 2 repositories listed
  Limited by the context window size of Large Language Models(LLMs), handling various tasks with input tokens exceeding the upper limit has been challenging, whether it is a simple direct retrieval task or a complex…
• RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generation
  16 Feb 2025 2 repositories listed Syntology ran 1 of 13 samples · 12 unverified · 2 pointer-only (licence)
  Large language models (LLMs) have achieved impressive performance on knowledge-intensive tasks, yet they often struggle with multi-step reasoning due to the unstructured nature of retrieved context.
• AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents
  9 Feb 2025 2 repositories listed
  To address this challenge, we introduce AutoAgent-a Fully-Automated and highly Self-Developing framework that enables users to create and deploy LLM agents through Natural Language Alone.
• WebWalker: Benchmarking LLMs in Web Traversal
  13 Jan 2025 2 repositories listed
  Extensive experimental results show that WebWalkerQA is challenging and demonstrates the effectiveness of RAG combined with WebWalker, through the horizontal and vertical integration in real-world scenarios.
• Eliza: A Web3 friendly AI Agent Operating System
  12 Jan 2025 2 repositories listed
  AI Agent, powered by large language models (LLMs) as its cognitive core, is an intelligent agentic system capable of autonomously controlling and determining the execution paths under user's instructions.
• Search-o1: Agentic Search-Enhanced Large Reasoning Models
  9 Jan 2025 2 repositories listed
  To address this limitation, we introduce \textbf{Search-o1}, a framework that enhances LRMs with an agentic retrieval-augmented generation (RAG) mechanism and a Reason-in-Documents module for refining retrieved…
• Jasper and Stella: distillation of SOTA embedding models
  26 Dec 2024 2 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  However, the embedding models that currently excel on text embedding benchmarks, like the Massive Text Embedding Benchmark (MTEB), often have numerous parameters and high vector dimensionality.
• Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework
  14 Nov 2024 2 repositories listed
  Within the TREC setup, we are able to calibrate our fully automatic process against a manual process whereby nuggets are created by human assessors semi-manually and then assigned manually to system answers.
• AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline
  28 Oct 2024 2 repositories listed
  Using LLMs (Large Language Models) in conjunction with external documents has made RAG (Retrieval-Augmented Generation) an essential technology.
• LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
  24 Oct 2024 2 repositories listed Syntology ran 0 of 20 samples · 20 unverified
  LoRANN is competitive with the leading graph-based algorithms and outperforms the state-of-the-art GPU ANN methods on high-dimensional data sets.

Syntology lines on 14 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.