Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:34:14.620879Z
Paper Citation Record · LEDGER
As of 7 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:34:14.620879Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T18:12:46.942777Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T08:20:32.119672Z
89 of 89 outbound references displayed
External citation measurements
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Observation e3ca6b5b-276f-44c2-bb3b-aa4777d58b0e · outbound
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
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Observation e557ef28-7ade-4e37-b652-8a7e2d026354 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Test case generation for agent-based models: A systematic literature review,
Reference 2
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Observation d7992564-574c-43d9-9548-326b43764cfe · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A review on test automation for test cases generation using nlp techniques,
Reference 3
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Observation 95ea05a7-8def-4256-a709-80f1353156d4 · outbound
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
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Observation 615e40e0-6f69-4fe2-bc9a-394154c0344b · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Smells in system user interactive tests,
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Observation b941e142-a573-4f05-8413-43c4909b7a5a · outbound
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
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Observation 32cdfc1d-00ad-4673-8b2a-399618ff4144 · outbound
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
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Observation 5f62474e-3b7c-495c-8613-c5b55929f152 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Requirements-driven automated software testing: A systematic review,
Reference 8
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Observation 94b096c3-eb6d-422f-97fd-a8ee7d572538 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Large language models for software engineering: Sur- vey and open problems,
Reference 9
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Observation 8589bcfd-da3a-4660-9c7a-3b8f8f7b4875 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Generative Artificial Intelligence for Software Engineering -- A Research Agenda
Reference 10
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Observation 27bbd167-83f3-4087-a9fe-71b1a1d3f69e · outbound
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
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Observation 8b1d6732-7ddc-440f-9994-b2379197e3f4 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs On the effectiveness of large language models in domain- specific code generation,
Reference 12
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Observation 0bc79f12-ce86-4e53-a3fe-16aa1a4581e7 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Enhancing large language models through external domain knowledge,
Reference 13
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Observation 3a4a42e3-ed78-4167-a80d-0ed4d0a3e8dd · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval- augmented generation for knowledge-intensive nlp tasks,
Reference 14
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Observation d38e586e-66aa-4584-90c7-3707f4200804 · outbound
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
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Observation 5cefd16e-cee8-4c6d-95e9-bcf164aea1ff · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Cohn, User stories applied: For agile software development
Reference 16
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Observation a94a6664-7a8a-4be5-b360-71a2f82e32c7 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Artefact Repository: Multi- Modal Requirements Data based Acceptance Criteria Generation using LLMs
Reference 17
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Observation 891ddf94-405c-4001-b4c4-84f5d7019143 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Evaluation of retrieval-augmented generation: A survey,
Reference 18
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Observation f75c4ed5-735e-4876-82b2-2388fa97841f · outbound
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
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Observation 7932f052-e82c-4290-b8e2-839fd9d940b3 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
Reference 20
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Observation 802589a2-8d22-4a93-bd16-f50ed23ee897 · outbound
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
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Observation 218bc2af-9bb2-404a-a8e4-4f6127258cbe · outbound
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
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Observation d694cae2-9b6d-478f-b91c-3e8491d570a4 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs A survey on rag meeting llms: Towards retrieval-augmented large language models,
Reference 23
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Observation ecce6e05-7308-4373-9ad3-e90bfd1d7a9d · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Improvements to bm25 and language models examined,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Using tf-idf to determine word relevance in document queries,
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Observation 75fd21f0-6747-4d4f-ab89-f7f10a633144 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Maximizing rag efficiency: A comparative analysis of rag methods,
Reference 26
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs COS-Mix: Cosine Similarity and Distance Fusion for Improved Information Retrieval
Reference 27
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Observation aac0992e-374c-4638-b053-4493a6ea7292 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs In-context retrieval-augmented language mod- els,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reference 29
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Observation 9aac474c-5315-4279-94fa-81bbd9350349 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Retrieval-Augmented Multimodal Language Modeling
Reference 30
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Observation bc502629-83e2-4271-ac0b-0aefb1e7e6b8 · outbound
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
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Observation 5a289cc5-d7cc-46ee-966d-2d62ed3b4098 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
Reference 32
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Observation 1c90880b-35d4-459b-a21f-8bf1cbc5e1c0 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Mastering the game of go without human knowledge,
Reference 33
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs MUSE: Modularizing Unsupervised Sense Embeddings
Reference 34
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Reference 35
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Balancing the Scales: Reinforcement Learning for Fair Classification
Reference 36
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Inferring lexicographically-ordered rewards from preferences,
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Reference 38
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Observation 36a0b4e8-50ac-4506-929d-f69b460d6c98 · outbound
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Reference 39
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Observation 5b28bf92-8db9-4868-bf74-048da193e1e3 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods
Reference 40
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Observation 81e637f6-ca8b-4188-bcde-5563b1c381dd · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges
Reference 41
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Observation 879a127f-aab8-44d0-a46e-1c835d4e3168 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Improving zero-shot LLM re-ranker with risk minimization,
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Observation 4c743990-c476-495f-a9e8-75e9326ec614 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Reducing requirements ambiguity via gamification: comparison with traditional techniques,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automated test case generation from requirements: A systematic literature review,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Regression test selection on system requirements,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Representation of knowledge from software requirements expressed in natural language,
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Reqcap: Hierarchical requirements modeling and test generation for industrial control systems,
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Reference 52
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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
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Automating acceptance testing with tool support,
Reference 54
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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
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Reference 56
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Reference 57
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Reference 58
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap
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Reference 60
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Reference 62
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Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Navigating LLM Ethics: Advancements, Challenges, and Future Directions
Reference 63
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Reference 64
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Reference 65
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Reference 66
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Reference 68
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Reference 71
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Reference 72
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Reference 73
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Reference 74
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Reference 76
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Reference 77
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Observation 7b67d165-4a5d-4e27-8a35-282670c69205 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations,
Reference 78
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Observation fddd4640-7cf4-4eb7-bb50-bd6034fc7309 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs [Online]
Reference 79
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Observation e27ac39e-9c5f-4c4e-96bb-87a405cdf98d · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues
Reference 80
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Observation 101c48b9-8511-4da7-b414-4a1d1c0ce3a4 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs [Online]
Reference 81
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Observation 7a405f4c-a688-4c9d-8af9-5d7816a594b0 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions
Reference 82
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Observation 541cb665-0c33-4ab4-ae07-4acd75d7bc42 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs GPT-4o System Card
Reference 83
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Observation 5fe66c84-cde1-4170-a51e-22ac00d73278 · outbound
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
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Observation 1dabb476-796a-40e7-a1a1-95629d87f9c2 · outbound
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
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Observation ec29f553-b3cb-49c0-94f3-cf4e6b19eab3 · outbound
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
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Observation f2315cbf-ec5d-4afe-8ab6-79f0941b39fa · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Ragas: Automated evaluation of retrieval augmented generation,
Reference 87
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Observation 32e30d31-31e0-41f0-b681-e73573ebb970 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Social desirability bias,
Reference 89
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Observation 2efc3b10-0a2b-464b-b297-81ecc23df344 · outbound
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs Requirements-Driven Automated Software Testing: A Systematic Review
Reference 2025
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Observation 838cd216-2183-4d63-85cd-018f5e2f043c · inbound
Guidelines for Empirical Studies in Software Engineering involving Large Language Models Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
Reference 139
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Observation 27def03a-09b1-42a4-ab3f-c71e7f2625ad · inbound
Guidelines for Empirical Studies in Software Engineering involving Large Language Models Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
Reference 139
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Observation cf2c2b15-db4c-4318-81ff-a8b6a6c29651 · inbound
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
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