Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers | Paper Citation Record

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers A comprehensive survey on legal summarization: Challenges and future directions

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Large language models robustness against perturbation: S

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Using llm (large language model) to improve efficiency in literature review for undergraduate research

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Robust tests for the equality of variances

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Efficient inference for noisy llm-as-a-judge evaluation

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Statistical comparisons of classifiers over multiple data sets

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Applicability of large language models and generative models for legal case judgement summarization

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This paper cites Explainability meets text summarization: A survey, in: Proceedings of the 17th International Natural Language Generation Conference, pp.

Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Explainability meets text summarization: A survey, in: Proceedings of the 17th International Natural Language Generation Conference, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Consistency Evaluation of News Article Summaries Generated by Large (and Small) Language Models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers TrustLLM: Trustworthiness in Large Language Models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Consistency analysis of chatgpt, in: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Context-Aware Sports Highlight Generation Leveraging Large Language Models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Llms cannot reliably judge (yet?): A comprehensive assessment on the robustness of llm-as-a-judge

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Do not abstain! identify and solve the uncertainty, in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (V olume 1: Long Papers), pp

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This paper cites Sumsurvey: An abstractive dataset of scientific survey papers for long document summarization, in: Findings of the ACL 2024, pp.

Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Sumsurvey: An abstractive dataset of scientific survey papers for long document summarization, in: Findings of the ACL 2024, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Low-resource court judgment summarization for common law systems

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Tools in the Loop: Quantifying Uncertainty of LLM Question Answering Systems That Use Tools

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Effectiveness in retrieving legal precedents: exploring text summarization and cutting-edge language models toward a cost-efficient approach

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers State of what art? a call for multi-prompt llm evaluation

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Abstractive text summarization using sequence-to-sequence rnns and beyond, in: Proceedings of the 20th SIGNLL conference on computational natural language learning, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Evaluating Variance in Visual Question Answering Benchmarks

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Efficient multi-prompt evaluation of llms, in: Proceedings of the 38th International Conference on Neural Information Processing Systems, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Leveraging large language models on the traditional scientific writing workflow, in: 2024 Conference on AI, Science, Engineering, and Technology (AIxSET), IEEE

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers How resilient are language models to text perturbations?, in: International Conference on Intelligent Data Engineering and Automated Learning, Springer

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Can You Trust LLM Judgments? Reliability of LLM-as-a-Judge

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers A coin flip for safety: Llm judges fail to reliably measure adversarial robustness

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Robustness of large language models to perturbations in text

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Legal text summarization via judicial syllogism with large language models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Artificial intelligence risk management framework (ai rmf 1.0).(2023)

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Evaluating the factual consistency of large language models through news summarization, in: Findings of the Association for Computational Linguistics: ACL 2023, pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Unresolved cited work

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Prompt engineering in consistency and reliability with the evidence-based guideline for llms

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Using llm-supported lecture summarization system to improve knowledge recall and student satisfaction

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Comparisons of various types of normality tests

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Event-based evaluation of abstractive news summarization, in: Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM2), pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Alignscore: Evaluating factual consistency with a unified alignment function, in: Proceedings of the 61st Annual Meeting of the ACL (V olume 1: Long Papers), pp

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers A systematic survey of text summarization: From statistical methods to large language models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers BERTScore: Evaluating Text Generation with BERT

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Benchmarking large language models for news summarization

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Trustworthy evaluation of large language models

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods

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Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers Assessing the accuracy of artificial intelligence-generated clinical summaries from ambulatory glaucoma subspecialty clinical encounters

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