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LLM-based applications are helping people write, and LLM-generated text is making its way into social media, journalism, and our classrooms.
Readability: A new approach
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Clichés: Avoid them like the plague
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Academic writing and authorial voice
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Automatically Classifying Edit Categories in Wikipedia Revisions. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing , David Yarowsky, Timothy Baldwin, Anna Korhonen, Karen Livescu, and Steven Bethard (Eds.). Association for Computational Linguistics, Seattle, Washington, USA, 578–589
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Continuous measurement scales in human evaluation of machine translation. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse . 33–41
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Politics and the English language
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Literary narrative and mental imagery: A view from embodied cognition
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Soylent: a word processor with a crowd inside
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Omission
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WearWrite: Crowd-Assisted Writing from Smartwatches. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16) . Association for Computing Machinery, New York, NY, USA, 3834–3846
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SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 10674–10695
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Self-alignment with instruction backtranslation
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Co-Writing Screenplays and Theatre Scripts with Language Models: Evaluation by Industry Professionals. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 355, 34 pages
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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Cited alongside, same era.
Deep reinforcement learning from human preferences
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Purple prose
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Writing fiction: A guide to narrative craft
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Fine-tuning language models from human preferences
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Predictive text encourages predictable writing. In Proceedings of the 25th International Conference on Intelligent User Interfaces (Cagliari, Italy) (IUI ’20) . Association for Computing Machinery, New York, NY, USA, 128–138
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Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 1877–1901
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Vishakh Padmakumar and He He. 2023 · 2023
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Why “why”? The Importance of Communicating Rationales for Edits in Collaborative Writing. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 616, 25 pages
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CoEdIT: Text Editing by Task-Specific Instruction Tuning. In Findings of the Association for Computational Linguistics: EMNLP 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, Singapore, 5274–5291
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Verbosity bias in preference labeling by large language models
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Improving Summarization with Human Edits. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 2604–2620
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Claude-3.5-Sonnet
Anthropic. 2024 · 2024
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Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’24) . Association for Computing Machinery, New York, NY, USA, Article 1044, 18 pages
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Automatic and Human-AI Interactive Text Generation (with a focus on Text Simplification and Revision). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts) , Luis Chiruzzo, Hung-yi Lee, and Leonardo Ribeiro (Eds.). Association for Computational Linguistics, Bangkok, Thailand, 3–4
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VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models
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The ethics of advanced ai assistants
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Books3 is the Internet’s Most Controversial AI Dataset
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A Robot Walks into a Bar: Can Language Models Serve as Creativity SupportTools for Comedy? An Evaluation of LLMs’ Humour Alignment with Comedians. In The 2024 ACM Conference on Fairness, Accountability, and Transparency . 1622–1636
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