Paper Citation Record · LEDGER

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation

As of 7 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 2 inbound Pith citation observations for arXiv:2508.20131.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.20131 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:04:06.893020Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:43.698445Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-10T11:30:19.582711Z

Reference resolution

21 of 21 outbound references displayed

verified exact1
verified fuzzy12
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5753453-dcf9-46c4-a50b-43c1f60a3bc6 · outbound

This paper cites GPT-4 Technical Report.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:04.809346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e56452c-011a-4b9d-8c89-91936662201a · outbound

This paper cites Evaluating open-source Large Language Models for automated fact-checking.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Evaluating open-source Large Language Models for automated fact-checking

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:05.100598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11695aac-3933-4e15-a2a4-95ac2ffafc1d · outbound

This paper cites Argumentative Large Language Models for Explainable and Contestable Claim Verification.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Argumentative Large Language Models for Explainable and Contestable Claim Verification

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:05.320748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da9c1045-2cdc-4338-882e-1fe521ce1208 · outbound

This paper cites Supposedly Equivalent Facts That Aren't? Entity Frequency in Pre-training Induces Asymmetry in LLMs.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Supposedly Equivalent Facts That Aren't? Entity Frequency in Pre-training Induces Asymmetry in LLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:05.419308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f73bd9a-a3b3-423a-ae3d-d8e491c03b72 · outbound

This paper cites Dense passage retrieval for open-domain question answer- ing.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Dense passage retrieval for open-domain question answer- ing

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:09.136315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1efad248-09cd-4831-8ff2-0c40008efde5 · outbound

This paper cites Re-rag: Improving open-domain qa performance and in- terpretability with relevance estimator in retrieval-augmented generation.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Re-rag: Improving open-domain qa performance and in- terpretability with relevance estimator in retrieval-augmented generation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.982496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 91baf3d1-345d-47ed-ab74-54b6b2e21d61 · outbound

This paper cites Explainable automated fact-checking for public health claims.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Explainable automated fact-checking for public health claims

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.812945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 43dab3dd-5f28-46ea-a696-927bcda8192d · outbound

This paper cites Knowledge conflicts for llms: A survey.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Knowledge conflicts for llms: A survey

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:07.748462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ce9367e-109e-4c73-87f3-6d9b89099d55 · outbound

This paper cites Worse than zero- shot? a fact-checking dataset for evaluating the robustness of rag against misleading retrievals.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Worse than zero- shot? a fact-checking dataset for evaluating the robustness of rag against misleading retrievals

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:06.462169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb784bfd-ad68-475a-8be3-e22a08af9165 · outbound

This paper cites Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:06.584593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffc748ae-d414-462b-8192-218a369c4094 · outbound

This paper cites Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-05T16:04:07.111427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 22a9d7b2-9ae0-42b2-945d-f5616f0dc12a · outbound

This paper cites Predicate-conditional conformalized answer sets for knowledge graph embeddings.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Predicate-conditional conformalized answer sets for knowledge graph embeddings

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:07.566453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ac2c3434-8eea-49fb-873f-d70552599a27 · outbound

This paper cites explanation.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation explanation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:07.431405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b307a5c7-1767-4647-8ca6-da62850b45e6 · outbound

This paper cites Step-by-step fact verification system for medical claims with explainable reasoning.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Step-by-step fact verification system for medical claims with explainable reasoning

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.004545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1e9fd559-36ff-4e9b-9927-9a34941b37e3 · outbound

This paper cites Balancing open-mindedness and conservativeness in quan- titative bipolar argumentation (and how to prove semantical from functional properties).

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Balancing open-mindedness and conservativeness in quan- titative bipolar argumentation (and how to prove semantical from functional properties)

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.245486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ae60091-e669-4a92-a0ad-dd0294260c9c · outbound

This paper cites Can retriever-augmented lan- guage models reason? the blame game between the retriever and the language model.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Can retriever-augmented lan- guage models reason? the blame game between the retriever and the language model

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:09.331772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 20a69559-bc43-4435-9688-699dfe3a6d51 · outbound

This paper cites Continuous dynamical systems for weighted bipolar argumentation.KR, 2018: 148–57,.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Continuous dynamical systems for weighted bipolar argumentation.KR, 2018: 148–57,

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.445558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf748ea1-2ca3-4de5-ac48-e3609e72c2d8 · outbound

This paper cites Shayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, and Sameer Singh.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Shayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, and Sameer Singh

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:08.675056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0dc593c3-5c60-4479-8058-5590eb8144a2 · outbound

This paper cites Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:06.177113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41dfb52b-5bd6-4360-9f6a-400f548de783 · outbound

This paper cites Leila Amgoud and Jonathan Ben-Naim.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Leila Amgoud and Jonathan Ben-Naim

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:09.515123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ba66f8d5-4ec3-4099-9e57-b4600e29d772 · outbound

This paper cites Argumentative Large Language Models for Explainable and Contestable Claim Verification.

ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation Argumentative Large Language Models for Explainable and Contestable Claim Verification

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T16:04:05.224633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4e79463e-ebc3-460b-9593-2242338aaa73 · inbound

ArbGraph: Conflict-Aware Evidence Arbitration for Reliable Long-Form Retrieval-Augmented Generation cites this paper.

ArbGraph: Conflict-Aware Evidence Arbitration for Reliable Long-Form Retrieval-Augmented Generation ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:30:19.584802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 21dfffd7-ac5c-4204-8f3c-ba63a1d4d4c9 · inbound

PURPOSE: Poisoning Conflict Resolution in RAG via Proxy-Fact-Grounded Updates cites this paper.

PURPOSE: Poisoning Conflict Resolution in RAG via Proxy-Fact-Grounded Updates ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:43.698445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.