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Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP) algorithms, aims to create concise and accurate summaries, thereby significantly reducing the human effort required in processing large volumes of text.
Language models are few-shot learners,
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G. Adams, A. Fabbri, F. Ladhak, E. Lehman, N. Elhadad, · 2023
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2023
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IDAS: Intent discovery with abstractive summarization,
M. De Raedt, F. Godin, T. Demeester, C. Develder, · 2023
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S. S. Manathunga, Y. A. Illangasekara, · 2023
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Radadapt: Radiology report summarization via lightweight domain adaptation of large language models,
D. V. Veen, C. V. Uden, M. Attias, A. Pareek, C. Blüthgen, M. Polacin, W. Chiu, J.-B. Delbrouck, J. M. Z. Chaves, C. P. Langlotz, A. S. Chaudhari, J. M. Pauly, · 2023
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Long document summarization with top-down and bottom-up inference,
B. Pang, E. Nijkamp, W. Kryscinski, S. Savarese, Y. Zhou, C. Xiong, · 2023
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Evaluating large language models on medical evidence summarization,
L. Tang, Z. Sun, B. Idnay, J. G. Nestor, A. Soroush, P. A. Elias, Z. Xu, Y. Ding, G. Durrett, J. F. Rousseau, C. Weng, Y. Peng, · 2023
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A systematic study and comprehensive evaluation of chatgpt on benchmark datasets,
M. T. R. Laskar, M. S. Bari, M. Rahman, M. A. H. Bhuiyan, S. Joty, J. X. Huang, · 2023
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2023
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2023
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T. Goyal, J. J. Li, G. Durrett, News summarization and evaluation in the era of gpt-3, 2023
2023
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2023
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2023
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G-eval: NLG evaluation using gpt-4 with better human alignment,
Y. Liu, D. Iter, Y. Xu, S. Wang, R. Xu, C. Zhu, · 2023
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2023
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2023
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2023
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2023
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Spec: A soft prompt-based calibration on performance variability of large language model in clinical notes summarization,
Y.-N. Chuang, R. Tang, X. Jiang, X. Hu, · 2024
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An iterative optimizing framework for radiology report summarization with chatgpt,
C. Ma, Z. Wu, J. Wang, S. Xu, Y. Wei, Z. Liu, F. Zeng, X. Jiang, L. Guo, X. Cai, S. Zhang, T. Zhang, D. Zhu, D. Shen, T. Liu, X. Li, · 2024
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2024
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Automatic semantic augmentation of language model prompts (for code summarization),
T. Ahmed, K. S. Pai, P. Devanbu, E. Barr, · 2024
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Distilled gpt for source code summarization,
C.-Y. Su, C. McMillan, · 2024
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Clipsyntel: Clip and llm synergy for multimodal question summarization in healthcare,
A. Ghosh, A. Acharya, R. Jain, S. Saha, A. Chadha, S. Sinha, · 2024
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Baichuan2-sum: Instruction finetune baichuan2-7b model for dialogue summarization,
J. Xiao, Y. Chen, Y. Ou, H. Yu, K. Shu, Y. Xiao, · 2024
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TriSum: Learning summarization ability from large language models with structured rationale,
P. Jiang, C. Xiao, Z. Wang, P. Bhatia, J. Sun, J. Han, · 2024
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Product description and QA assisted self-supervised opinion summarization,
T. Siledar, R. Rangaraju, S. Muddu, S. Banerjee, A. Patil, S. Singh, M. Chelliah, N. Garera, S. Nath, P. Bhattacharyya, · 2024
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Integrate the essence and eliminate the dross: Fine-grained self-consistency for free-form language generation,
X. Wang, Y. Li, S. Feng, P. Yuan, B. Pan, H. Wang, Y. Hu, K. Li, · 2024
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Code summarization without direct access to code - towards exploring federated llms for software engineering,
J. Kumar, S. Chimalakonda, · 2024
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Multimodal ai-based summarization and storytelling for soccer on social media,
M. H. Sarkhoosh, S. Gautam, C. Midoglu, S. S. Sabet, P. Halvorsen, · 2024
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Improving faithfulness of large language models in summarization via sliding generation and self-consistency,
T. Li, Z. Li, Y. Zhang, · 2024
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Unveiling the power of integration: Block diagram summarization through local-global fusion,
S. Bhushan, E.-S. Jung, M. Lee, · 2024
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Comprehensive abstractive comment summarization with dynamic clustering and chain of thought,
L. Zhang, B. Zou, J. Yi, A. Aw, · 2024
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Impossible distillation for paraphrasing and summarization: How to make high-quality lemonade out of small, low-quality model,
J. Jung, P. West, L. Jiang, F. Brahman, X. Lu, J. Fisher, T. Sorensen, Y. Choi, · 2024
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XrayGPT: Chest radiographs summarization using large medical vision-language models,
O. C. Thawakar, A. M. Shaker, S. S. Mullappilly, H. Cholakkal, R. M. Anwer, S. Khan, J. Laaksonen, F. Khan, · 2024
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Chatcite: Llm agent with human workflow guidance for comparative literature summary,
Y. Li, L. Chen, A. Liu, K. Yu, L. Wen, · 2024
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Towards a robust retrieval-based summarization system,
S. Liu, J. Wu, J. Bao, W. Wang, N. Hovakimyan, C. G. Healey, · 2024
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UIUC_BioNLP at BioLaySumm: An extract-then-summarize approach augmented with Wikipedia knowledge for biomedical lay summarization,
Z. You, S. Radhakrishna, S. Ming, H. Kilicoglu, · 2024
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Augmenting low-resource cross-lingual summarization with progression-grounded training and prompting,
J. Ma, Y. Huang, L. Wang, X. Huang, H. Peng, Z. Yu, P. Yu, · 2024
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2024
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Benchmarking large language models for news summarization,
T. Zhang, F. Ladhak, E. Durmus, P. Liang, K. McKeown, T. B. Hashimoto, · 2024
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Extracting and summarizing evidence of suicidal ideation in social media contents using large language models,
L. Gyanendro Singh, J. Mao, R. Mutalik, S. E. Middleton, · 2024
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No perspective, no perception!! perspective-aware healthcare answer summarization,
G. Naik, S. Chandakacherla, S. Yadav, M. S. Akhtar, · 2024
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Investigating hallucinations in pruned large language models for abstractive summarization,
G. Chrysostomou, Z. Zhao, M. Williams, N. Aletras, · 2024
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Chain-of-descriptions: Improving code llms for vhdl code generation and summarization,
P. Vijayaraghavan, A. Nitsure, C. Mackin, L. Shi, S. Ambrogio, A. Haran, V. Paruthi, A. Elzein, D. Coops, D. Beymer, T. Baldwin, E. Degan, · 2024
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2024
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3a-cot: an attend-arrange-abstract chain-of-thought for multi-document summarization,
Y. Zhang, S. Gao, Y. Huang, Z. Yu, K. Tan, · 2024
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2024
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Aligning llm agents by learning latent preference from user edits,
G. Gao, A. Taymanov, E. Salinas, P. Mineiro, D. Misra, · 2024
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Agent planning with world knowledge model,
S. Qiao, R. Fang, N. Zhang, Y. Zhu, X. Chen, S. Deng, Y. Jiang, P. Xie, F. Huang, H. Chen, · 2024
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Leveraging large language models for NLG evaluation: Advances and challenges,
Z. Li, X. Xu, T. Shen, C. Xu, J.-C. Gu, Y. Lai, C. Tao, S. Ma, · 2024
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One prompt to rule them all: LLMs for opinion summary evaluation,
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GPTScore: Evaluate as you desire,
J. Fu, S.-K. Ng, Z. Jiang, P. Liu, · 2024
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Language models can evaluate themselves via probability discrepancy,
T. Xia, B. Yu, Y. Wu, Y. Chang, C. Zhou, · 2024
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Bayesian calibration of win rate estimation with LLM evaluators,
Y. Gao, G. Xu, Z. Wang, A. Cohan, · 2024
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Automatic large language model evaluation via peer review,
Z. Chu, Q. Ai, Y. Tu, H. Li, Y. Liu, · 2024
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FineSurE: Fine-grained summarization evaluation using LLMs,
H. Song, H. Su, I. Shalyminov, J. Cai, S. Mansour, · 2024
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ACUEval: Fine-grained hallucination evaluation and correction for abstractive summarization,
D. Wan, K. Sinha, S. Iyer, A. Celikyilmaz, M. Bansal, R. Pasunuru, · 2024
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2024
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DEBATE: Devil’s advocate-based assessment and text evaluation,
A. Kim, K. Kim, S. Yoon, · 2024
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DataHacks at PerAnsSumm 2025: LoRA-driven prompt engineering for perspective aware span identification and summarization,
V. Nawander, C. R. Nerella, · 2025
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Reasoning models don’t always say what they think,
Y. Chen, J. Benton, A. Radhakrishnan, J. U. C. Denison, J. Schulman, A. Somani, P. Hase, M. W. F. R. V. Mikulik, S. Bowman, J. L. J. Kaplan, et al., · 2025
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2025
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2025
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2025
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Fully abstractive approach to guided summarization,
P.-E. Genest, G. Lapalme, · 2069
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A discourse-aware attention model for abstractive summarization of long documents,
A. Cohan, F. Dernoncourt, D. S. Kim, T. Bui, S. Kim, W. Chang, N. Goharian, · 2097
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