ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation | Paper Citation Record

Observation 6b038aea-d958-4ccd-81c9-79b7c6a7710e · outbound

This paper cites Requirements Elicitation: A Survey of Techniques, Approaches, and Tools,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Requirements Elicitation: A Survey of Techniques, Approaches, and Tools,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:16.114197Z

Source-reported events for the cited work

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

Observation 254eac53-5071-47d8-b30d-1989306260f6 · outbound

This paper cites Ambiguity as a resource to dis- close tacit knowledge,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Ambiguity as a resource to dis- close tacit knowledge,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:16.000715Z

Source-reported events for the cited work

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

Observation 5352e017-14d2-479d-9925-6adc096e817e · outbound

This paper cites Unpacking Tacit Knowledge for Requirements En- gineering,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Unpacking Tacit Knowledge for Requirements En- gineering,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.797557Z

Source-reported events for the cited work

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

Observation ea0fdca1-0720-4c01-8ca6-1df0820cfd14 · outbound

This paper cites The en- gagement between knowledge transfer and requirements engineering,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation The en- gagement between knowledge transfer and requirements engineering,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.656141Z

Source-reported events for the cited work

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

Observation 90c7d0ff-f21a-4222-a098-52ef91dca796 · outbound

This paper cites Naming the pain in requirements engineering: Contemporary problems, causes, and effects in practice,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Naming the pain in requirements engineering: Contemporary problems, causes, and effects in practice,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.492526Z

Source-reported events for the cited work

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

Observation 2adcfee7-04c9-4b72-9102-f04ff8cfa17e · outbound

This paper cites Requirements elicitation: Towards the unknown unknowns,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Requirements elicitation: Towards the unknown unknowns,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.396585Z

Source-reported events for the cited work

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

Observation 9ec54480-1310-46ca-b637-53e931e89d8e · outbound

This paper cites Detecting Requirements Smells With Deep Learning: Experiences, Challenges and Future Work,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Detecting Requirements Smells With Deep Learning: Experiences, Challenges and Future Work,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.220985Z

Source-reported events for the cited work

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

Observation 39abeb90-b415-44a3-89a4-864ac1ba7494 · outbound

This paper cites Easy Approach to Requirements Syntax (EARS),.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Easy Approach to Requirements Syntax (EARS),

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:15.097543Z

Source-reported events for the cited work

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

Observation f51e5caf-e95e-4321-81ed-07d29e09e035 · outbound

This paper cites The Importance of Modeling Social Factors of Language: Theory and Practice,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation The Importance of Modeling Social Factors of Language: Theory and Practice,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.945616Z

Source-reported events for the cited work

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

Observation e7bbdd43-d958-4eb4-a9f8-5a8f202557b6 · outbound

This paper cites ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.832200Z

Source-reported events for the cited work

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

Observation e109e3a6-be1c-4e3c-a56b-e42664bd1e27 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:01.912534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4318c6a-ef14-4dfd-9926-7e5f1b717c34 · outbound

This paper cites Improving Language Understanding by Generative Pre-Training,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Improving Language Understanding by Generative Pre-Training,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.666612Z

Source-reported events for the cited work

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

Observation 0385b1d0-77fc-427f-aca6-60249c82fd52 · outbound

This paper cites ISO/IEC/IEEE 29148:2018,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation ISO/IEC/IEEE 29148:2018,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.586509Z

Source-reported events for the cited work

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

Observation cd034ace-df0c-45ed-896b-6a29560daff9 · outbound

This paper cites Large Language Models for Software Engineering: A Systematic Literature Review,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Large Language Models for Software Engineering: A Systematic Literature Review,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.357745Z

Source-reported events for the cited work

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

Observation 4c61e0e8-5dc2-42bb-a82e-84f886bb0b1a · outbound

This paper cites Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:48:08.455999Z

Source-reported events for the cited work

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

Observation de659a86-02eb-4d45-882f-efbe05a8f1c7 · outbound

This paper cites PPT: Pre-trained Prompt Tuning for Few-shot Learning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.268463Z

Source-reported events for the cited work

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Observation 32c63915-04b6-4b0e-baa4-ecb4afd449a6 · outbound

This paper cites Context-faithful Prompting for Large Language Models.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Context-faithful Prompting for Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.369164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda36880-dd04-4a0e-91d6-c06d84737c18 · outbound

This paper cites Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.469330Z

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Observation 4df64c3e-463d-4036-8ef3-d208509a3a8f · outbound

This paper cites Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.545145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47eb3e06-6a3a-4c51-99bc-f7fcf34788cf · outbound

This paper cites Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.235327Z

Source-reported events for the cited work

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

Observation 04ce10cc-d04e-4e4e-b665-a63a4822d023 · outbound

This paper cites Investigating ChatGPT’s Potential to Assist in Requirements Elicitation Processes,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Investigating ChatGPT’s Potential to Assist in Requirements Elicitation Processes,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:14.050193Z

Source-reported events for the cited work

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

Observation 9e429d65-2cda-4f55-81f7-07a132fccac6 · outbound

This paper cites Mitigating Large Language Model Hallucination with Faithful Finetuning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.849746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffc55f16-4e27-4803-8c8a-29d97de63b2b · outbound

This paper cites Two-stage LLM Fine-tuning with Less Specialization and More Generalization.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Two-stage LLM Fine-tuning with Less Specialization and More Generalization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:02.906858Z

Source-reported events for the cited work

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Observation a6b3fc43-2b13-4fd3-bb70-67cc314d0419 · outbound

This paper cites RECOVER: Toward Requirements Generation from Stakeholders' Conversations.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation RECOVER: Toward Requirements Generation from Stakeholders' Conversations

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:48:08.228493Z

Source-reported events for the cited work

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

Observation d2d0e0b4-064b-4058-a474-98fd201d313e · outbound

This paper cites Washizaki, Guide to the Software Engineering Body of Knowledge (SWEBOK Guide), 4th ed.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Washizaki, Guide to the Software Engineering Body of Knowledge (SWEBOK Guide), 4th ed

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:13.955826Z

Source-reported events for the cited work

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

Observation b732d29a-e99c-4f6a-879e-9a96c0a026c3 · outbound

This paper cites of Excellence for Software & Systems Traceability, “Coest,” http://sarec.nd.edu/coest/datasets.html, 2002.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation of Excellence for Software & Systems Traceability, “Coest,” http://sarec.nd.edu/coest/datasets.html, 2002

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:13.815652Z

Source-reported events for the cited work

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

Observation 40573ace-63d0-4b2a-bcf7-4cc56f3b9a2a · outbound

This paper cites frieden84/nlp4re-reqeval: Second release,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation frieden84/nlp4re-reqeval: Second release,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:13.662848Z

Source-reported events for the cited work

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

Observation ff06812f-1cda-4be2-bf94-4d65108df70c · outbound

This paper cites Pure: A dataset of public re- quirements documents,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Pure: A dataset of public re- quirements documents,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:03.501326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71174143-5a52-479f-a5e2-80bf97093b28 · outbound

This paper cites Extracting Software Requirements from Unstructured Documents,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Extracting Software Requirements from Unstructured Documents,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:13.470178Z

Source-reported events for the cited work

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

Observation f423e1c3-e61a-46d9-9670-2ca49f5145dd · outbound

This paper cites Knauss, S.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Knauss, S

Reference 30

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:48:13.368483Z

Source-reported events for the cited work

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

Observation 9242f4b5-f7a7-451d-b512-e7284d811e94 · outbound

This paper cites Software requirement risk prediction dataset,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Software requirement risk prediction dataset,

Reference 31

Resolution: verified exact; doi, observed 2026-08-07T14:48:07.486119Z

Source-reported events for the cited work

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

Observation ee7accd2-3085-499e-994d-41a652784bc1 · outbound

This paper cites Rfp attachment #1: Functional and nonfunctional requirements for vhcures 3.0,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Rfp attachment #1: Functional and nonfunctional requirements for vhcures 3.0,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:13.123649Z

Source-reported events for the cited work

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

Observation 6047ad41-8559-4b1f-82a5-be7e04c1bfb8 · outbound

This paper cites Requirements Classification with Interpretable Machine Learning and Dependency Parsing,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Requirements Classification with Interpretable Machine Learning and Dependency Parsing,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:12.925659Z

Source-reported events for the cited work

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

Observation e5557a18-40f6-4b65-ab15-bb071ff41f54 · outbound

This paper cites The requirements tracing on target (retro).net dataset,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation The requirements tracing on target (retro).net dataset,

Reference 34

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:48:12.755872Z

Source-reported events for the cited work

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

Observation dc906674-cd6b-45c6-ac9b-e68950cc514a · outbound

This paper cites Eye tracking experiments data set - linking use cases and associated requirements: On the impact of linking variants on reading behavior,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Eye tracking experiments data set - linking use cases and associated requirements: On the impact of linking variants on reading behavior,

Reference 35

Resolution: verified exact; doi, observed 2026-08-07T14:48:07.334778Z

Source-reported events for the cited work

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

Observation 2818ddd4-d3c3-4533-a160-53a3f935a580 · outbound

This paper cites Eclipse public license-v2.0,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Eclipse public license-v2.0,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:12.511112Z

Source-reported events for the cited work

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

Observation e2a80a32-1d37-401c-a5a2-fd6314dddb9b · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:04.301653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 140be840-2400-4936-a47a-b06670d33be7 · outbound

This paper cites Continual Pre-Training of Large Language Models: How to (re)warm your model?.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Continual Pre-Training of Large Language Models: How to (re)warm your model?

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:12.299668Z

Source-reported events for the cited work

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

Observation 0ea8112b-4a23-4c7a-ab95-ea35ae899ed1 · outbound

This paper cites Language Models are Few- Shot Learners,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Language Models are Few- Shot Learners,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:12.105550Z

Source-reported events for the cited work

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

Observation 81a4cfb5-6edb-41b7-a1ee-8c9f2f1cc0fb · outbound

This paper cites Efficient Few-Shot Learning Without Prompts.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Efficient Few-Shot Learning Without Prompts

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:04.612158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e92fad-a853-4e5b-9ef6-7bf1ea866a69 · outbound

This paper cites Pre-Trained Language Models and Their Applications,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Pre-Trained Language Models and Their Applications,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:11.847522Z

Source-reported events for the cited work

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

Observation d0250604-1cfa-4be8-b6b8-d694de4564ff · outbound

This paper cites Improving language understanding with unsupervised learning,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Improving language understanding with unsupervised learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:11.616960Z

Source-reported events for the cited work

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

Observation c35c967b-2f26-4043-b4a7-aa55d3c8f710 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:04.904589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac68a921-5014-41f4-a422-3ad93db79c92 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Overcoming catastrophic forgetting in neural networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:11.441194Z

Source-reported events for the cited work

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

Observation 1f046f6d-06ef-4672-b495-93d9a8961071 · outbound

This paper cites Task Arithmetic with LoRA for Continual Learning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Task Arithmetic with LoRA for Continual Learning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.104837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d443d7ae-462e-43cd-a4bf-84db3cef1a6d · outbound

This paper cites Investigating the Catastrophic Forgetting in Multimodal Large Language Models.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Investigating the Catastrophic Forgetting in Multimodal Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.164135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fac4bddb-0480-4d44-8798-60e2bf00ee42 · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.273599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e7145f9-a8a0-4417-99d7-cf72f53450cb · outbound

This paper cites Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.365651Z

Source-reported events for the cited work

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Observation f4f926ed-f5fc-4e51-9405-8dcb1180f9df · outbound

This paper cites Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspective.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspective

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.437752Z

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Observation f98bf562-46b6-4644-8d60-4a6d14bcba99 · outbound

This paper cites Llama 2: Open Foundation and Fine- Tuned Chat Models | Research - AI at Meta,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Llama 2: Open Foundation and Fine- Tuned Chat Models | Research - AI at Meta,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:11.265533Z

Source-reported events for the cited work

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

Observation 8944ebfe-b4bc-4891-94fd-5563b6e0a826 · outbound

This paper cites Mistral 7B.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Mistral 7B

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.596035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20cb3732-4e73-4b8f-8c2f-076d0b1b4f72 · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Zephyr: Direct Distillation of LM Alignment

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.651365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2883f232-2fbc-401a-94c4-0ddf540294e9 · outbound

This paper cites Falcon-40B: an open large language model with state-of-the-art performance,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Falcon-40B: an open large language model with state-of-the-art performance,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:11.064785Z

Source-reported events for the cited work

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

Observation c67b7a9c-191b-486d-a31e-8db481a8e3ba · outbound

This paper cites Hugging face,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Hugging face,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:10.845992Z

Source-reported events for the cited work

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

Observation 98ddcf07-8542-4946-8c39-c94928f5ebde · outbound

This paper cites Training Compute-Optimal Large Language Models.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Training Compute-Optimal Large Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:05.867138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f468721-39cf-4c47-8d27-5e2b05fa5e26 · outbound

This paper cites How to do human evaluation: A brief introduction to user studies in NLP,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation How to do human evaluation: A brief introduction to user studies in NLP,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:10.608261Z

Source-reported events for the cited work

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

Observation 4455a048-c1dd-4043-8edd-184b92768121 · outbound

This paper cites Within-subjects designs: To use or not to use?.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Within-subjects designs: To use or not to use?

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:10.228229Z

Source-reported events for the cited work

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

Observation d8d57c17-cb25-4e72-811c-ce23ec1f90e4 · outbound

This paper cites Towards Evaluation Guidelines for Empirical Studies involving LLMs.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Towards Evaluation Guidelines for Empirical Studies involving LLMs

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:06.130019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad01e2d-b663-40b0-872a-56fbbb7c425a · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation BERTScore: Evaluating Text Generation with BERT

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:06.247929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation facf88a5-5471-4549-9adf-46c1e1977e7a · outbound

This paper cites FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metricsfor Automatic Text Generation.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metricsfor Automatic Text Generation

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:48:07.861013Z

Source-reported events for the cited work

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

Observation 5fdd8d89-0706-410d-8547-d7c71cf24e94 · outbound

This paper cites Bleu: a Method for Automatic Evaluation of Machine Translation,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Bleu: a Method for Automatic Evaluation of Machine Translation,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:10.031755Z

Source-reported events for the cited work

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

Observation a5123e1f-bd6d-4406-be54-8b263b74a86d · outbound

This paper cites ROUGE: A Package for Automatic Evaluation of Sum- maries,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation ROUGE: A Package for Automatic Evaluation of Sum- maries,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.851119Z

Source-reported events for the cited work

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

Observation 2e05bb44-a167-4df8-991f-2001186a5e2d · outbound

This paper cites A Study of Translation Edit Rate with Targeted Human Annotation,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A Study of Translation Edit Rate with Targeted Human Annotation,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.709100Z

Source-reported events for the cited work

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

Observation 138b0ec0-4c9a-4f37-8866-ff9ad650ae63 · outbound

This paper cites Exploring Correlation Between ROUGE and Hu- man Evaluation on Meeting Summaries,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Exploring Correlation Between ROUGE and Hu- man Evaluation on Meeting Summaries,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.572081Z

Source-reported events for the cited work

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

Observation 376d9dc4-6662-4b7d-891f-78174924c677 · outbound

This paper cites Comparing Automatic Evaluation Measures for Image Description,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Comparing Automatic Evaluation Measures for Image Description,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.436432Z

Source-reported events for the cited work

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

Observation ad4a671a-fc01-44dd-b266-9250f87a8ca7 · outbound

This paper cites Why We Need New Evaluation Metrics for NLG,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Why We Need New Evaluation Metrics for NLG,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.321588Z

Source-reported events for the cited work

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

Observation 1cf6706a-a972-4eb0-899f-44906e722334 · outbound

This paper cites Well-Read Students Learn Better: On the Importance of Pre-training Compact Models.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:48:06.850072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95658cde-b02b-428d-a49b-edafafc60926 · outbound

This paper cites A call for greater use of nonparametric statistics.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A call for greater use of nonparametric statistics

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.203672Z

Source-reported events for the cited work

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

Observation 0733aad7-d276-4d2b-91f7-33f4f7d656af · outbound

This paper cites A practical guide for using statistical tests to assess randomized algorithms in software engineering,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A practical guide for using statistical tests to assess randomized algorithms in software engineering,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:09.092081Z

Source-reported events for the cited work

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

Observation 6d6e1b67-3931-4962-a666-9cc516062595 · outbound

This paper cites A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:08.937196Z

Source-reported events for the cited work

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

Observation 58e446d6-9725-45ab-b0de-80541e40c61b · outbound

This paper cites A Simple Sequentially Rejective Multiple Test Procedure,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A Simple Sequentially Rejective Multiple Test Procedure,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:08.776587Z

Source-reported events for the cited work

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

Observation 6fa26a46-5aad-4317-b646-e6c5fd5ca394 · outbound

This paper cites A systematic review of statistical power in software engineering experiments,.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation A systematic review of statistical power in software engineering experiments,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:48:08.615430Z

Source-reported events for the cited work

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

Observation aa5d9301-0685-46a0-a8f8-05d8057cd163 · outbound

This paper cites Available: https://doi .org/10.5281/zenodo.4471411.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Available: https://doi .org/10.5281/zenodo.4471411

Reference 2021

Resolution: verified exact; doi, observed 2026-08-07T14:48:07.650824Z

Source-reported events for the cited work

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

Coverage vector

Reference resolution

Outbound references

Pith citing papers