LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration | Paper Citation Record

Observation c94dfeb0-4b10-4f44-bf8c-3e4e618c368a · outbound

This paper cites The power of assessment feedback in teaching and learning: a narrative review and synthesis of the literature.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration The power of assessment feedback in teaching and learning: a narrative review and synthesis of the literature

Reference 1

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Observation b08d3a66-4a8a-4f0d-96ea-7c271c1ee447 · outbound

This paper cites Planning for the unknown: Local government strategies from the fiscal year 2021 budget season in response to the covid-19 pandemic.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Planning for the unknown: Local government strategies from the fiscal year 2021 budget season in response to the covid-19 pandemic

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.977069Z

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Observation 31ab4bbd-564b-4511-bb06-eb897c22adf2 · outbound

This paper cites The value and effectiveness of feedback in improving students' learning and professionalizing teaching in higher education.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration The value and effectiveness of feedback in improving students' learning and professionalizing teaching in higher education

Reference 3

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Observation 7e75f048-2abd-443f-bc70-150a509ea2c6 · outbound

This paper cites Why Does the Effective Context Length of LLMs Fall Short?.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Why Does the Effective Context Length of LLMs Fall Short?

Reference 4

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Observation 2d002b3c-f1af-4b1a-a458-e44e6ff7593e · outbound

This paper cites Combining LLMs with Logic-Based Framework to Explain MCTS.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Combining LLMs with Logic-Based Framework to Explain MCTS

Reference 5

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Observation 3192c3b6-9ed4-4e1e-b634-f58b0411dbb8 · outbound

This paper cites Bounded model checking of signal temporal logic properties using syntactic separation.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Bounded model checking of signal temporal logic properties using syntactic separation

Reference 6

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Observation a4bebf1d-2033-4d5e-8d7b-7afd3ade63f0 · outbound

This paper cites Cityspec: An intelligent assistant system for requirement specification in smart cities.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Cityspec: An intelligent assistant system for requirement specification in smart cities

Reference 7

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Observation 82bb25e5-a491-4f94-92fe-43e168732b88 · outbound

This paper cites An intelligent assistant for converting city requirements to formal specification.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration An intelligent assistant for converting city requirements to formal specification

Reference 8

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Observation 6fe00d47-0a8b-4da8-9691-bfcc0392f27f · outbound

This paper cites Cityspec with shield: A secure intelligent assistant for requirement formalization.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Cityspec with shield: A secure intelligent assistant for requirement formalization

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.917651Z

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Observation 25eb9076-7bbd-4ede-8758-afa2801db9b3 · outbound

This paper cites Benchmarking large language models in retrieval-augmented generation.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Benchmarking large language models in retrieval-augmented generation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.904565Z

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Observation bb8a96fe-3553-4ff1-9259-1203a1bf2b47 · outbound

This paper cites Auto311: A confidence-guided automated system for non-emergency calls.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Auto311: A confidence-guided automated system for non-emergency calls

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.891300Z

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Observation bd8185c1-ce80-4881-b5db-e5eb261cde06 · outbound

This paper cites Sim911: Towards effective and equitable 9-1-1 dispatcher training with an llm-enabled simulation.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Sim911: Towards effective and equitable 9-1-1 dispatcher training with an llm-enabled simulation

Reference 12

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Observation 95270411-994a-402e-9a85-f9da88d792d3 · outbound

This paper cites Scaling instruction-finetuned language models.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Scaling instruction-finetuned language models

Reference 13

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Observation 236b5ee6-0946-4d87-a534-4571a1bf2334 · outbound

This paper cites nl2spec: interactively translating unstructured natural language to temporal logics with large language models.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration nl2spec: interactively translating unstructured natural language to temporal logics with large language models

Reference 14

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Observation 8ba31872-2609-4d57-8f27-ad9d3ad4553c · outbound

This paper cites Gemini-flash-thinking: Multi-modal reasoning with external memory.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Gemini-flash-thinking: Multi-modal reasoning with external memory

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.843869Z

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Observation 68f2a7fc-41ef-4461-a30c-15ea68b00c2b · outbound

This paper cites Deepseek-v3: Scaling open large language models with moe, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Deepseek-v3: Scaling open large language models with moe, 2024

Reference 16

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Observation ac7ef087-d7a6-4225-837d-365f55f5543d · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.820877Z

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Observation 326b05f6-8471-4a69-8569-2d2117aba836 · outbound

This paper cites Exploring Context Window of Large Language Models via Decomposed Positional Vectors.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Exploring Context Window of Large Language Models via Decomposed Positional Vectors

Reference 18

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Observation cc234777-879c-4da0-a525-7e22d421d5ee · outbound

This paper cites An automated system repair framework with signal temporal logic.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration An automated system repair framework with signal temporal logic

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.808593Z

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Observation 7de13c20-4641-455f-8b7e-cdfae9da87f9 · outbound

This paper cites Gemma 2: Improving open language models at a practical size, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Gemma 2: Improving open language models at a practical size, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.795658Z

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Observation 15add7da-9352-4fab-b372-1ce7e1fcc71a · outbound

This paper cites Intelligent tutoring systems.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Intelligent tutoring systems

Reference 21

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Observation 9969d227-867b-4886-8863-418b6e97068b · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Large Language Models Cannot Self-Correct Reasoning Yet

Reference 22

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Observation 754a1cee-a759-4a06-b732-b9668f8f8c28 · outbound

This paper cites America's 911 workforce is in crisis, 2023.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration America's 911 workforce is in crisis, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.771048Z

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Observation 30b1890c-4058-4775-a4a2-b591c3381aef · outbound

This paper cites Call volume and quality assurance challenges in u.s.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Call volume and quality assurance challenges in u.s

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.758863Z

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Observation 97660553-87ef-4860-9e9e-805231dc898f · outbound

This paper cites Can large language models reason and plan? Annals of the New York Academy of Sciences , 1534(1):15--18, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Can large language models reason and plan? Annals of the New York Academy of Sciences , 1534(1):15--18, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.746799Z

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Observation 77f1e9c6-dc3f-4462-b8e7-56d316892dd6 · outbound

This paper cites BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

Reference 26

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This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 27

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Observation 22f69344-c4e7-4ee8-a694-53fea09ff221 · outbound

This paper cites Deductive verification of chain-of-thought reasoning.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Deductive verification of chain-of-thought reasoning

Reference 28

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Observation 8ffed7b3-8381-4e8c-96ae-6d81611069c0 · outbound

This paper cites Lost in the middle: How language models use long contexts.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Lost in the middle: How language models use long contexts

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.709941Z

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Observation 4938c3c4-09e6-48d4-943a-1cb85a76f57e · outbound

This paper cites Data sets, modeling, and decision making in smart cities: A survey.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Data sets, modeling, and decision making in smart cities: A survey

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.695183Z

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Observation f267fa0a-b3e3-461d-9f61-671343551534 · outbound

This paper cites Monitoring temporal properties of continuous signals.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Monitoring temporal properties of continuous signals

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.682216Z

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Observation 643d080d-067c-4947-86cd-5b8e88287bcc · outbound

This paper cites When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1

Reference 32

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Observation a0d17f2b-7779-4f52-98cb-dd28e5ba70b5 · outbound

This paper cites A critical review of simulation-based medical education research: 2003--2009.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration A critical review of simulation-based medical education research: 2003--2009

Reference 33

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Observation 4050c57f-4c4f-47e5-9dc2-c132eb7ff2f9 · outbound

This paper cites Llama 3.2: Revolutionizing edge ai and vision with open, customizable models, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Llama 3.2: Revolutionizing edge ai and vision with open, customizable models, 2024

Reference 34

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Observation ca801f2a-64b9-4f74-8d5a-2e9d1fd02869 · outbound

This paper cites SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 35

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Observation 3e07374c-c0ac-4b41-82ee-dd1a0218699a · outbound

This paper cites Explainable reinforcement learning: A survey and comparative review.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Explainable reinforcement learning: A survey and comparative review

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.649666Z

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Observation 5935fa6d-1d03-4444-99e2-e85c65517ed1 · outbound

This paper cites FDNY Issue Brief , 2025.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration FDNY Issue Brief , 2025

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.638274Z

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Observation 149cd4ec-4c55-41ae-a72e-f6bbb5144f10 · outbound

This paper cites Gpt-4o system card, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Gpt-4o system card, 2024

Reference 38

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Observation b0977d8f-4bd3-4755-8dbe-903fb7547cdd · outbound

This paper cites Openai o1 system card, 2024.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Openai o1 system card, 2024

Reference 39

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Observation 1d3b603b-c731-4067-8c09-3b908f75605e · outbound

This paper cites Enhancing text classification through llm-driven active learning and human annotation.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Enhancing text classification through llm-driven active learning and human annotation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.609198Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 89bf9539-79d8-46c9-b59a-7846e4705b39 · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 41

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Observation a32f4086-2faa-4323-8706-91ec1a58e3d4 · outbound

This paper cites Language models that seek for knowledge: Modular search and generation for open-domain question answering.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Language models that seek for knowledge: Modular search and generation for open-domain question answering

Reference 42

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation af19df05-11e0-4af4-86e0-3e4115acf609 · outbound

This paper cites Clinical debriefing: a concept analysis.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Clinical debriefing: a concept analysis

Reference 43

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b24ae4ed-bf0d-4f3d-8e17-7feac76b16ef · outbound

This paper cites Language models don't always say what they think: unfaithful explanations in chain-of-thought prompting.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Language models don't always say what they think: unfaithful explanations in chain-of-thought prompting

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.571790Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7a657fd3-63d9-4107-b596-e34f9067b8b9 · outbound

This paper cites The behavior of tutoring systems.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration The behavior of tutoring systems

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.558752Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ebc86075-6f01-494f-a494-b2c59c4bac1d · outbound

This paper cites Searching for best practices in retrieval-augmented generation.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Searching for best practices in retrieval-augmented generation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.546770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e3d89924-1c9a-4247-851d-8e877429ad30 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Chain-of-thought prompting elicits reasoning in large language models

Reference 47

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Observation fb1116b1-ffe1-416d-99e0-c9b3ed2ba50f · outbound

This paper cites Empirical study of llm fine-tuning for text classification in legal document review.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Empirical study of llm fine-tuning for text classification in legal document review

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.526697Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 526f0aba-948c-4fb7-9728-26a8ae6f8e28 · outbound

This paper cites Mastering symbolic operations: Augmenting language models with compiled neural networks.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Mastering symbolic operations: Augmenting language models with compiled neural networks

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.513517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d62657d9-23c1-434c-8ff6-825a7c96022d · outbound

This paper cites A Comparative Study on Reasoning Patterns of OpenAI's o1 Model.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration A Comparative Study on Reasoning Patterns of OpenAI's o1 Model

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T23:45:01.325139Z

Source-reported events for the cited work

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Observation 0f89b967-0e43-4294-9075-7022a5a3413f · outbound

This paper cites Star: Bootstrapping reasoning with reasoning.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration Star: Bootstrapping reasoning with reasoning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:45:01.499245Z

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Observation cbe6e559-d264-4072-8c2a-c7c24cec2b85 · outbound

This paper cites write newline.

LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration write newline

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T23:45:01.334167Z

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