Paper Citation Record · LEDGER

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection

As of 23 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.18952.

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

pith.paper-citation-record.v1
2507.18952 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:07:57.499127Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

verified exact15
verified fuzzy7
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47e84ea0-1a6b-4f39-9547-23a83be95f08 · outbound

This paper cites Language Models are Few-Shot Learners.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Language Models are Few-Shot Learners

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.322338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6edde1b9-11b2-4a19-88d8-3dc9d860ca98 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection PaLM: Scaling Language Modeling with Pathways

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.327007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3522d47-c007-4b2e-9023-9b89b3aeebce · outbound

This paper cites Training language models to follow instructions with human feedback.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Training language models to follow instructions with human feedback

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.330690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 861f9442-f53e-4b4c-a5f5-893b09e826d4 · outbound

This paper cites Artificial intelligence for context-aware visual change detection in software test automation,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Artificial intelligence for context-aware visual change detection in software test automation,

Reference 4

Resolution: verified exact; raw_fallback, observed 2026-08-15T18:07:58.111511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1d51f457-32fb-4d3d-a71e-e6964859a99c · outbound

This paper cites Analysis of collective response reveals that covid-19-related activities start from the end of 2019 in mainland china,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Analysis of collective response reveals that covid-19-related activities start from the end of 2019 in mainland china,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.338251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1930f4fc-8bd6-4496-9088-0905503f03da · outbound

This paper cites Voice Recognition Robot with Real-Time Surveillance and Automation.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Voice Recognition Robot with Real-Time Surveillance and Automation

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:58.010174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4bd6a533-3b81-4022-8b06-a47f4bfaec12 · outbound

This paper cites HADES: Homologous Automated Document Exploration and Summarization.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection HADES: Homologous Automated Document Exploration and Summarization

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.991248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 55a182d0-d82a-4239-bc7a-a308268f9bf9 · outbound

This paper cites Semi-automatic data enhancement for document-level relation extraction with distant supervision from large language models,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Semi-automatic data enhancement for document-level relation extraction with distant supervision from large language models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.255770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4cd00b6d-ea1f-49ff-9ac5-dd21f53d88e8 · outbound

This paper cites Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.354694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0326ebc-2b7a-4bf8-8137-e4d97a50b055 · outbound

This paper cites Improving Vietnamese Legal Document Retrieval using Synthetic Data.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Improving Vietnamese Legal Document Retrieval using Synthetic Data

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.959296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69e3d5ef-b1b1-4a65-a812-bff22b91ddfb · outbound

This paper cites Large Language Model Prompt Chaining for Long Legal Document Classification.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Large Language Model Prompt Chaining for Long Legal Document Classification

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.368267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1e381e0-39a1-4cfb-9022-ff083fefa0ff · outbound

This paper cites Automated Argument Generation from Legal Facts.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Automated Argument Generation from Legal Facts

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.918482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5214e2c1-0bf7-4882-98dd-95ff1ea4e6eb · outbound

This paper cites Docinfer: Document-level natural language inference using optimal evidence selection,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Docinfer: Document-level natural language inference using optimal evidence selection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.242502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation de8288f9-a143-4ee2-a8e8-d74ac3d1a604 · outbound

This paper cites DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.383664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c13af37-0648-4948-9e3e-f8065db6d6e3 · outbound

This paper cites ANLS* -- A Universal Document Processing Metric for Generative Large Language Models.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection ANLS* -- A Universal Document Processing Metric for Generative Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.387765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f4b9582-7a57-4811-9d9e-6134a47d469f · outbound

This paper cites ChuLo: Chunk-Level Key Information Representation for Long Document Understanding.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection ChuLo: Chunk-Level Key Information Representation for Long Document Understanding

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.876159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b9c1bfa8-974e-43a4-a661-fa83b1e3bf92 · outbound

This paper cites Unifying vision, text, and layout for universal document processing,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Unifying vision, text, and layout for universal document processing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.227796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d25cc316-60a1-4253-ac56-bbb493dca375 · outbound

This paper cites Domain-Agnostic Neural Architecture for Class Incremental Continual Learning in Document Processing Platform.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Domain-Agnostic Neural Architecture for Class Incremental Continual Learning in Document Processing Platform

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.857155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6b401cfb-609f-47c5-b532-5aa769b4fa40 · outbound

This paper cites The future of document indexing: GPT and Donut revolutionize table of content processing.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection The future of document indexing: GPT and Donut revolutionize table of content processing

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.836904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3179c36-1699-41ea-812c-ad0bb0f61732 · outbound

This paper cites RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.409371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 630f017d-157a-4ead-a637-3ff4f55a6236 · outbound

This paper cites Adapting Large Language Models for Document-Level Machine Translation.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Adapting Large Language Models for Document-Level Machine Translation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.414356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1df21ffe-3b44-4a6b-b576-494d2b7a46cd · outbound

This paper cites Semantic Similarity Matching for Patent Documents Using Ensemble BERT-related Model and Novel Text Processing Method.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Semantic Similarity Matching for Patent Documents Using Ensemble BERT-related Model and Novel Text Processing Method

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.788921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a0f4d6f7-fa2f-435b-84c1-aa3f725b01ff · outbound

This paper cites Intelligent System for Automated Molecular Patent Infringement Assessment.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Intelligent System for Automated Molecular Patent Infringement Assessment

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.769174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5041d29e-e8b0-4739-9c4b-5ec5d6bc4ae2 · outbound

This paper cites blockLAW: Blockchain Technology for Legal Automation and Workflow -- Cyber Ethics and Cybersecurity Platforms.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection blockLAW: Blockchain Technology for Legal Automation and Workflow -- Cyber Ethics and Cybersecurity Platforms

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.750486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 073ed571-6d9f-4093-8f62-3fa4589120af · outbound

This paper cites Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.733824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c0aac3d5-8df1-413c-9a86-9174c2f8fa64 · outbound

This paper cites Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate Pairs.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate Pairs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.434664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba2e46c6-a973-4345-ba06-dd7780cd4a77 · outbound

This paper cites Enabling Discriminative Reasoning in LLMs for Legal Judgment Prediction.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Enabling Discriminative Reasoning in LLMs for Legal Judgment Prediction

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.438585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 395e066c-e977-4d93-9e62-538b52e16dbd · outbound

This paper cites Better Call GPT, Comparing Large Language Models Against Lawyers.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Better Call GPT, Comparing Large Language Models Against Lawyers

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.442693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 536ebbaf-21a2-4e11-becd-381acda5b703 · outbound

This paper cites Agents on the Bench: Large Language Model Based Multi Agent Framework for Trustworthy Digital Justice.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Agents on the Bench: Large Language Model Based Multi Agent Framework for Trustworthy Digital Justice

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.446474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdb03237-9e51-478b-abdf-91f436868bc1 · outbound

This paper cites An element is worth a thousand words: Enhancing legal case retrieval by incorporating legal elements,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection An element is worth a thousand words: Enhancing legal case retrieval by incorporating legal elements,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.213612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 35626180-a12d-4c32-b6e4-9bb5faa06282 · outbound

This paper cites NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.667283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5c1c1c29-f3c9-40a5-8b83-18fa061ad537 · outbound

This paper cites Unlocking Context Constraints of LLMs: Enhancing Context Efficiency of LLMs with Self-Information-Based Content Filtering.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Unlocking Context Constraints of LLMs: Enhancing Context Efficiency of LLMs with Self-Information-Based Content Filtering

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.456469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b6695cf-93a2-4d3f-8ba2-51104e92d298 · outbound

This paper cites ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.460567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bdb9bdd-2fc3-4eaa-9ecf-9661ea612cc3 · outbound

This paper cites WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.464100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 323ca673-8fed-4b87-a5d3-4c0aa9632086 · outbound

This paper cites WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.468422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3054e58c-3041-4d2d-85f5-e4c10cabfcfd · outbound

This paper cites Gamewikisum: a novel large multi- document summarization dataset,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Gamewikisum: a novel large multi- document summarization dataset,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.201147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation afc98869-7916-4ca2-9592-ef87ecb183b4 · outbound

This paper cites Long Text and Multi-Table Summarization: Dataset and Method.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Long Text and Multi-Table Summarization: Dataset and Method

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.476121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a5b8a90-7e18-45c4-ab10-289822a95c2a · outbound

This paper cites Solving multiple-instance and multiple- part learning problems with decision trees and rule sets. application to the mutagenesis problem,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Solving multiple-instance and multiple- part learning problems with decision trees and rule sets. application to the mutagenesis problem,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.188531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 025dca2d-70ef-4828-99ee-b7a27c3dc1ee · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Reading digits in natural images with unsupervised feature learning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:07:58.174808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8bb82273-9a5f-4172-ba31-c09fe9957c4c · outbound

This paper cites The GitHub Development Workflow Automation Ecosystems.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection The GitHub Development Workflow Automation Ecosystems

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.583903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 17de2a31-7624-49f0-941a-8b30f8c61088 · outbound

This paper cites Hyper-automation-The next peripheral for automation in IT industries.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Hyper-automation-The next peripheral for automation in IT industries

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:07:57.565173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 93d9b222-fe47-43c6-a2b2-2c14194bb038 · outbound

This paper cites LLM-Aided Testbench Generation and Bug Detection for Finite-State Machines.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection LLM-Aided Testbench Generation and Bug Detection for Finite-State Machines

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.495476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7dff37b-a814-48a9-abae-f585b1edf44f · outbound

This paper cites A Comprehensive Survey on Machine Learning Driven Material Defect Detection.

Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection A Comprehensive Survey on Machine Learning Driven Material Defect Detection

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T18:07:57.499127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.