Paper Citation Record · LEDGER

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining

As of 17 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.14619.

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

pith.paper-citation-record.v1
2507.14619 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:58:10.266877Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

16 of 16 outbound references displayed

verified exact2
verified fuzzy9
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9b18863b-b46c-45c6-8a2a-b0573e6b99fc · outbound

This paper cites Retrieval-Augmented Gen- eration for Knowledge-Intensive NLP Tasks.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Retrieval-Augmented Gen- eration for Knowledge-Intensive NLP Tasks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.676835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1887d50a-9b69-4fb0-a662-d9416dcea992 · outbound

This paper cites A statistical interpretation of term specificity and its appli- cation in retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining A statistical interpretation of term specificity and its appli- cation in retrieval

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.664261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9253e669-b54d-439d-8cc5-7f7b37552e92 · outbound

This paper cites Some Simple Effective Approxima- tions to the 2-Poisson Model for Probabilistic Weighted Retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Some Simple Effective Approxima- tions to the 2-Poisson Model for Probabilistic Weighted Retrieval

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.650903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation aace0ec8-9622-4a69-89e4-4952887a952e · outbound

This paper cites Sentence-BERT: Sentence Embeddings us- ing Siamese BERT-Networks.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Sentence-BERT: Sentence Embeddings us- ing Siamese BERT-Networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.638114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ab6f5979-b053-4efb-b36e-ad07876bbd2d · outbound

This paper cites Universal Sentence Encoder for English.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Universal Sentence Encoder for English

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.625057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f55c8d41-3e43-4f7e-b88d-6b4965a7e9f9 · outbound

This paper cites Legal Document Retrieval using Document Vector Embeddings and Deep Learning.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Legal Document Retrieval using Document Vector Embeddings and Deep Learning

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:58:10.558575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8b5d0f80-11ff-4cf8-8e0b-feb608ba65fc · outbound

This paper cites Attentive deep neural networks for legal doc- ument retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Attentive deep neural networks for legal doc- ument retrieval

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.611844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c4cd241-4338-40ad-b7b0-9a37b176f1de · outbound

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

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:58:10.539496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e08813ff-8d32-48fa-81a5-ec3d2b61288b · outbound

This paper cites Learning Dense Representa- tions for Entity Retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Learning Dense Representa- tions for Entity Retrieval

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.598555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ff5c5485-b3d7-4847-b22e-1337f7f31df6 · outbound

This paper cites Efficient Natural Language Response Suggestion for Smart Reply.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Efficient Natural Language Response Suggestion for Smart Reply

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:09.778476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf19c493-e984-4590-8d4c-2852bf9dc971 · outbound

This paper cites Multi-Stage Document Ranking with BERT.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Multi-Stage Document Ranking with BERT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:09.857993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c8c3bd2-be20-4568-a8cc-7e6cf41a3223 · outbound

This paper cites In Defense of Cross-Encoders for Zero-Shot Retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining In Defense of Cross-Encoders for Zero-Shot Retrieval

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:09.978044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb92b9b4-2d6f-4f4e-b955-b613b1b6ac61 · outbound

This paper cites T wente-BMS-NLP at PerspectiveArg 2024: Combining Bi-Encoder and Cross-Encoder for Argument Retrieval.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining T wente-BMS-NLP at PerspectiveArg 2024: Combining Bi-Encoder and Cross-Encoder for Argument Retrieval

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.585193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 04b8d076-45e0-49ef-b020-6bbc11406346 · outbound

This paper cites ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:10.060116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e640c074-eb44-4d7e-a712-574fc177fd7f · outbound

This paper cites Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:10.170063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 809c065b-88ab-4201-acbf-384556bac164 · outbound

This paper cites PhoRanker: A Cross-encoder Model for Vietnamese Text Rank- ing.

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining PhoRanker: A Cross-encoder Model for Vietnamese Text Rank- ing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:58:10.571804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.