Paper Citation Record · LEDGER

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs

As of 21 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 3 inbound Pith citation observations for arXiv:2508.06888.

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

pith.paper-citation-record.v1
2508.06888 v1

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:34:14.620879Z

measured 92 of 92 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T18:12:46.942777Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T08:20:32.119672Z

Reference resolution

89 of 89 outbound references displayed

verified exact5
verified fuzzy45
unresolved38
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3ca6b5b-276f-44c2-bb3b-aa4777d58b0e · outbound

This paper cites Automatic creation of acceptance tests by extracting conditionals from requirements: Nlp approach and case study,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automatic creation of acceptance tests by extracting conditionals from requirements: Nlp approach and case study,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.066984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e557ef28-7ade-4e37-b652-8a7e2d026354 · outbound

This paper cites Test case generation for agent-based models: A systematic literature review,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Test case generation for agent-based models: A systematic literature review,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.193751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7992564-574c-43d9-9548-326b43764cfe · outbound

This paper cites A review on test automation for test cases generation using nlp techniques,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A review on test automation for test cases generation using nlp techniques,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.396291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95ea05a7-8def-4256-a709-80f1353156d4 · outbound

This paper cites What makes agile test artifacts useful? an activity-based quality model from a practitioners’ perspective,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs What makes agile test artifacts useful? an activity-based quality model from a practitioners’ perspective,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.610785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 615e40e0-6f69-4fe2-bc9a-394154c0344b · outbound

This paper cites Smells in system user interactive tests,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Smells in system user interactive tests,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.810601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b941e142-a573-4f05-8413-43c4909b7a5a · outbound

This paper cites Automated acceptance tests as software requirements: An experiment to compare the applicability of fit tables and gherkin language,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automated acceptance tests as software requirements: An experiment to compare the applicability of fit tables and gherkin language,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:13.957581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32cdfc1d-00ad-4673-8b2a-399618ff4144 · outbound

This paper cites Comprehensive evaluation and insights into the use of large language models in the automation of behavior-driven development acceptance test formulation,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Comprehensive evaluation and insights into the use of large language models in the automation of behavior-driven development acceptance test formulation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.084233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f62474e-3b7c-495c-8613-c5b55929f152 · outbound

This paper cites Requirements-driven automated software testing: A systematic review,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Requirements-driven automated software testing: A systematic review,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.089242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94b096c3-eb6d-422f-97fd-a8ee7d572538 · outbound

This paper cites Large language models for software engineering: Sur- vey and open problems,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Large language models for software engineering: Sur- vey and open problems,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.138903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8589bcfd-da3a-4660-9c7a-3b8f8f7b4875 · outbound

This paper cites Generative Artificial Intelligence for Software Engineering -- A Research Agenda.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Generative Artificial Intelligence for Software Engineering -- A Research Agenda

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.202420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27bbd167-83f3-4087-a9fe-71b1a1d3f69e · outbound

This paper cites Domain knowledge is all you need: A field deployment of llm-powered test case generation in fintech domain,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Domain knowledge is all you need: A field deployment of llm-powered test case generation in fintech domain,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.581903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8b1d6732-7ddc-440f-9994-b2379197e3f4 · outbound

This paper cites On the effectiveness of large language models in domain- specific code generation,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs On the effectiveness of large language models in domain- specific code generation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.573193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0bc79f12-ce86-4e53-a3fe-16aa1a4581e7 · outbound

This paper cites Enhancing large language models through external domain knowledge,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Enhancing large language models through external domain knowledge,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.564239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3a4a42e3-ed78-4167-a80d-0ed4d0a3e8dd · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.355361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d38e586e-66aa-4584-90c7-3707f4200804 · outbound

This paper cites Generating test scenarios from nl requirements using retrieval-augmented llms: An industrial study,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Generating test scenarios from nl requirements using retrieval-augmented llms: An industrial study,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.357956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cefd16e-cee8-4c6d-95e9-bcf164aea1ff · outbound

This paper cites Cohn, User stories applied: For agile software development.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Cohn, User stories applied: For agile software development

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.544190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a94a6664-7a8a-4be5-b360-71a2f82e32c7 · outbound

This paper cites Artefact Repository: Multi- Modal Requirements Data based Acceptance Criteria Generation using LLMs.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Artefact Repository: Multi- Modal Requirements Data based Acceptance Criteria Generation using LLMs

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.535917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 891ddf94-405c-4001-b4c4-84f5d7019143 · outbound

This paper cites Evaluation of retrieval-augmented generation: A survey,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Evaluation of retrieval-augmented generation: A survey,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.518925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f75c4ed5-735e-4876-82b2-2388fa97841f · outbound

This paper cites Available: https://anonymous.4open.science/r/ Multi-Modal-Requirements-Data-based-Acceptance-Criteria-Generation-using-LLMs-1279/.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Available: https://anonymous.4open.science/r/ Multi-Modal-Requirements-Data-based-Acceptance-Criteria-Generation-using-LLMs-1279/

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.527525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7932f052-e82c-4290-b8e2-839fd9d940b3 · outbound

This paper cites Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.426103Z

Source-reported events for the cited work

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Observation 802589a2-8d22-4a93-bd16-f50ed23ee897 · outbound

This paper cites A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.423146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 218bc2af-9bb2-404a-a8e4-4f6127258cbe · outbound

This paper cites Reveal: Retrieval-augmented visual-language pre-training with multi-source multimodal knowledge memory,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Reveal: Retrieval-augmented visual-language pre-training with multi-source multimodal knowledge memory,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.511144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d694cae2-9b6d-478f-b91c-3e8491d570a4 · outbound

This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A survey on rag meeting llms: Towards retrieval-augmented large language models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.429675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecce6e05-7308-4373-9ad3-e90bfd1d7a9d · outbound

This paper cites Improvements to bm25 and language models examined,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Improvements to bm25 and language models examined,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.494458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36b1f104-d84f-41ed-9769-b8f5b3782baa · outbound

This paper cites Using tf-idf to determine word relevance in document queries,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Using tf-idf to determine word relevance in document queries,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.502734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75fd21f0-6747-4d4f-ab89-f7f10a633144 · outbound

This paper cites Maximizing rag efficiency: A comparative analysis of rag methods,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Maximizing rag efficiency: A comparative analysis of rag methods,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.486245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5167e69-1b08-4cb9-972a-381c61896eba · outbound

This paper cites COS-Mix: Cosine Similarity and Distance Fusion for Improved Information Retrieval.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs COS-Mix: Cosine Similarity and Distance Fusion for Improved Information Retrieval

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:34:15.065075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aac0992e-374c-4638-b053-4493a6ea7292 · outbound

This paper cites In-context retrieval-augmented language mod- els,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs In-context retrieval-augmented language mod- els,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.477722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c4ecee51-675a-498a-a5b3-7c379977717b · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 29

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Source-reported events for the cited work

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Observation 9aac474c-5315-4279-94fa-81bbd9350349 · outbound

This paper cites Retrieval-Augmented Multimodal Language Modeling.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval-Augmented Multimodal Language Modeling

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.457752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc502629-83e2-4271-ac0b-0aefb1e7e6b8 · outbound

This paper cites MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.454155Z

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Unavailable: canonical work link unavailable.

Observation 5a289cc5-d7cc-46ee-966d-2d62ed3b4098 · outbound

This paper cites RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.463965Z

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Observation 1c90880b-35d4-459b-a21f-8bf1cbc5e1c0 · outbound

This paper cites Mastering the game of go without human knowledge,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Mastering the game of go without human knowledge,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.468918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 652157eb-bf10-49cd-a4e0-522da0f8d5f5 · outbound

This paper cites MUSE: Modularizing Unsupervised Sense Embeddings.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs MUSE: Modularizing Unsupervised Sense Embeddings

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:34:15.007859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ae3abca-aaf2-4445-b79e-359b2315caaa · outbound

This paper cites RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style

Reference 35

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Source-reported events for the cited work

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Observation bba0fa89-f40c-42ed-b4e3-14691f5cd2ee · outbound

This paper cites Balancing the Scales: Reinforcement Learning for Fair Classification.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Balancing the Scales: Reinforcement Learning for Fair Classification

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:34:14.995765Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa9a46c5-956d-4383-b829-66ef27e67970 · outbound

This paper cites Inferring lexicographically-ordered rewards from preferences,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Inferring lexicographically-ordered rewards from preferences,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.460629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e57d647d-c45f-4c8d-8daf-a9bf780f2275 · outbound

This paper cites HelpSteer2-Preference: Complementing Ratings with Preferences.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs HelpSteer2-Preference: Complementing Ratings with Preferences

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.482448Z

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Observation 36a0b4e8-50ac-4506-929d-f69b460d6c98 · outbound

This paper cites Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.479640Z

Source-reported events for the cited work

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Observation 5b28bf92-8db9-4868-bf74-048da193e1e3 · outbound

This paper cites LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.488858Z

Source-reported events for the cited work

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Observation 81e637f6-ca8b-4188-bcde-5563b1c381dd · outbound

This paper cites Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.485583Z

Source-reported events for the cited work

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Observation 879a127f-aab8-44d0-a46e-1c835d4e3168 · outbound

This paper cites Improving zero-shot LLM re-ranker with risk minimization,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Improving zero-shot LLM re-ranker with risk minimization,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.452380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4ec7286b-97c4-44bd-9f17-f3f3576a2388 · outbound

This paper cites Generative Verifiers: Reward Modeling as Next-Token Prediction.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Generative Verifiers: Reward Modeling as Next-Token Prediction

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.492134Z

Source-reported events for the cited work

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Observation 4c743990-c476-495f-a9e8-75e9326ec614 · outbound

This paper cites Reducing requirements ambiguity via gamification: comparison with traditional techniques,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Reducing requirements ambiguity via gamification: comparison with traditional techniques,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.436029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8a9abadd-f341-4682-ba77-7e2bb1372526 · outbound

This paper cites Automated test case generation from requirements: A systematic literature review,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automated test case generation from requirements: A systematic literature review,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.444241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a65184df-5c05-4ba6-812b-100c13975ea6 · outbound

This paper cites Regression test selection on system requirements,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Regression test selection on system requirements,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.419374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0c030af9-c71f-4019-97a9-27658c9c558b · outbound

This paper cites Gam- ify4lexamb: a gamification-based approach to address lexical ambiguity in natural language requirements,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Gam- ify4lexamb: a gamification-based approach to address lexical ambiguity in natural language requirements,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.427891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b60298ad-cbc0-472b-bd4a-1c93c039d4a4 · outbound

This paper cites Representation of knowledge from software requirements expressed in natural language,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Representation of knowledge from software requirements expressed in natural language,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.402457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e3db38a0-055c-4e73-8be1-a369c1b33b1b · outbound

This paper cites Reqcap: Hierarchical requirements modeling and test generation for industrial control systems,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Reqcap: Hierarchical requirements modeling and test generation for industrial control systems,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.411236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation acbe9a5b-3c75-4482-b41a-3be442b2e957 · outbound

This paper cites A multi- case study of agile requirements engineering and the use of test cases as requirements,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A multi- case study of agile requirements engineering and the use of test cases as requirements,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.385638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9c51a277-d62c-4824-88db-0194036eac6b · outbound

This paper cites Aat4irs: automated acceptance testing for industrial robotic systems,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Aat4irs: automated acceptance testing for industrial robotic systems,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.394176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 61bc4f40-8159-476a-88cf-44f3ea7e086b · outbound

This paper cites Torc: test plan optimiza- tion by requirements clustering,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Torc: test plan optimiza- tion by requirements clustering,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.368835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a64095e7-c374-43f4-b6e1-68f9bcd848d0 · outbound

This paper cites Exploring llms impact on student-created user stories and acceptance testing in software development,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Exploring llms impact on student-created user stories and acceptance testing in software development,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.377279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1f998b46-cb04-4b3f-9e7d-453a4d21f2c9 · outbound

This paper cites Automating acceptance testing with tool support,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automating acceptance testing with tool support,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.352306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 38dba389-35b0-4f33-a149-560d8f10ef75 · outbound

This paper cites Automatic generation of acceptance test cases from use case specifications: an nlp-based approach,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automatic generation of acceptance test cases from use case specifications: an nlp-based approach,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.360422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation efa8d247-5762-4f27-85ef-f3bba00e5312 · outbound

This paper cites V ogelsang and J.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs V ogelsang and J

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.335076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4aae31a4-d415-414f-b52d-58c925256d4f · outbound

This paper cites Advancing requirements engineering through generative ai: Assessing the role of llms,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Advancing requirements engineering through generative ai: Assessing the role of llms,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.343815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c6862454-1ab4-40c6-8bd2-39c8459607d0 · outbound

This paper cites Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:34:14.932109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f11b2b7-91a6-4263-b047-13c430ffd7b7 · outbound

This paper cites Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.538267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5a9a1d7-5faf-45a8-9fc4-0caeaf590bee · outbound

This paper cites XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.547049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60187040-796e-46b2-b31e-a1d92165ba5a · outbound

This paper cites APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.544195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef593d0-f6d0-48a5-8f36-67f6f24d42bc · outbound

This paper cites Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.552925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6533ee1-6bed-4449-ad80-7d31ba8c4bbf · outbound

This paper cites Navigating LLM Ethics: Advancements, Challenges, and Future Directions.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Navigating LLM Ethics: Advancements, Challenges, and Future Directions

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.550111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82a84ad9-9366-4425-8785-85ee85b0d672 · outbound

This paper cites Llama-3.2-3B-Instruct,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Llama-3.2-3B-Instruct,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.326721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 32704343-ce54-4c6b-9dfd-1f276ac28391 · outbound

This paper cites An information bottleneck perspective for effec- tive noise filtering on retrieval-augmented generation,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs An information bottleneck perspective for effec- tive noise filtering on retrieval-augmented generation,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.555970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bbb6787-d015-40ba-84bf-5b7e1897de55 · outbound

This paper cites HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.564153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8454114b-a5dd-49d0-b624-39b05f9624e2 · outbound

This paper cites Screenshot-to-code,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Screenshot-to-code,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.317665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 485662a3-00bc-40ff-a960-1db75e639e0b · outbound

This paper cites all-MiniLM-L12-v2 ,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs all-MiniLM-L12-v2 ,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.301628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5a9423d1-01a1-4f8e-b12d-b57430fb0c85 · outbound

This paper cites dse-phi3-docmatix-v2,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs dse-phi3-docmatix-v2,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.309642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5aa5b4d2-472f-4ec3-8a4f-65d0444c7909 · outbound

This paper cites [Online].

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs [Online]

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.276243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b596ad10-2571-4a86-99ea-f11818b9b9c8 · outbound

This paper cites Available: https://huggingface.co/sentence-transformers/ all-MiniLM-L12-v2.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Available: https://huggingface.co/sentence-transformers/ all-MiniLM-L12-v2

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.293099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fdb987cc-7dc1-4702-bb79-952c24aceaf8 · outbound

This paper cites Llama-3.1-8B-Instruct,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Llama-3.1-8B-Instruct,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.284544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation edd32aa8-a11b-4b3e-a255-6705defad145 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.586491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aec56296-0a5d-4169-8fd2-255d49bcfa0a · outbound

This paper cites A technique for the measurement of attitudes.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A technique for the measurement of attitudes

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.267583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d535ffe-1197-42be-9692-6f48e725fd67 · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.583620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c1d82c7-49b7-4a55-b6c4-6a4d6c7573ae · outbound

This paper cites Survey of code search based on deep learning,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Survey of code search based on deep learning,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.250656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8cfbbf79-a2f6-41db-9894-1338e104fc32 · outbound

This paper cites A Survey on Retrieval-Augmented Text Generation.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A Survey on Retrieval-Augmented Text Generation

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.589249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b67d165-4a5d-4e27-8a35-282670c69205 · outbound

This paper cites Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.259334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fddd4640-7cf4-4eb7-bb50-bd6034fc7309 · outbound

This paper cites [Online].

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs [Online]

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.233148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e27ac39e-9c5f-4c4e-96bb-87a405cdf98d · outbound

This paper cites Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:34:14.682780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 101c48b9-8511-4da7-b414-4a1d1c0ce3a4 · outbound

This paper cites [Online].

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs [Online]

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.241827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7a405f4c-a688-4c9d-8af9-5d7816a594b0 · outbound

This paper cites Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.609921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 541cb665-0c33-4ab4-ae07-4acd75d7bc42 · outbound

This paper cites GPT-4o System Card.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs GPT-4o System Card

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.604851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fe66c84-cde1-4170-a51e-22ac00d73278 · outbound

This paper cites Combining similarity features and deep representation learning for stance detection in the context of checking fake news,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Combining similarity features and deep representation learning for stance detection in the context of checking fake news,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.224084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1dabb476-796a-40e7-a1a1-95629d87f9c2 · outbound

This paper cites Systematic Evaluation of LLM-as-a-Judge in LLM Alignment Tasks: Explainable Metrics and Diverse Prompt Templates.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Systematic Evaluation of LLM-as-a-Judge in LLM Alignment Tasks: Explainable Metrics and Diverse Prompt Templates

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-05T22:34:14.617849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec29f553-b3cb-49c0-94f3-cf4e6b19eab3 · outbound

This paper cites Open llms are necessary for current private adaptations and outperform their closed alternatives,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Open llms are necessary for current private adaptations and outperform their closed alternatives,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.214998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f2315cbf-ec5d-4afe-8ab6-79f0941b39fa · outbound

This paper cites Ragas: Automated evaluation of retrieval augmented generation,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Ragas: Automated evaluation of retrieval augmented generation,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.205521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 32e30d31-31e0-41f0-b681-e73573ebb970 · outbound

This paper cites Social desirability bias,.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Social desirability bias,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:34:15.196414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2efc3b10-0a2b-464b-b297-81ecc23df344 · outbound

This paper cites Requirements-Driven Automated Software Testing: A Systematic Review.

Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Requirements-Driven Automated Software Testing: A Systematic Review

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T22:34:15.187132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 838cd216-2183-4d63-85cd-018f5e2f043c · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs

Reference 139

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:02:52.632885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 27def03a-09b1-42a4-ab3f-c71e7f2625ad · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs

Reference 139

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:20:32.121951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf2c2b15-db4c-4318-81ff-a8b6a6c29651 · inbound

LLMCFG-TGen: Using LLM-Generated Control Flow Graphs to Automatically Create Test Cases from Use Cases cites this paper.

LLMCFG-TGen: Using LLM-Generated Control Flow Graphs to Automatically Create Test Cases from Use Cases Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T18:12:46.942777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.