--- title: "Natural language processing — papers, page 17" description: "Natural language processing: 2421 papers of the Elamur Research library · page 17 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/17/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/17/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/) / page 17 # 💬 Natural language processing 2421 papers · page 17 of 97 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Computational linguistics from the ACL Anthology and arXiv: language models, information extraction, dialogue, evaluation. [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [16](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) **17** [18](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) - [Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/) — Reid Pryzant, Dan Iter, Jerry Li, et al. · 2023 - [Beyond Concatenative Morphology: Applying OntoLex-Morph to Maltese](https://md.research.elamur.ai/free/en/papers/aclbulk-2023-ionov-beyond-concatenative-morphology-applying-ontolex/) — Maxim Ionov, Mike Rosner · 2023 - [C-Pack: Packed Resources For General Chinese Embeddings](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/) — Shitao Xiao, Zheng Liu, Peitian Zhang, et al. · 2023 - [Can AI-Generated Text be Reliably Detected?](https://md.research.elamur.ai/free/en/papers/sadasivan-2023-ai-generated-text-reliably-detected/) — Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al. · 2023 - [Can GPT-3 Perform Statutory Reasoning?](https://md.research.elamur.ai/free/en/papers/blair-2023-stanek-gpt-3-perform-statutory-reasoning/) — Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme · 2023 - [Certifying LLM Safety against Adversarial Prompting](https://md.research.elamur.ai/free/en/papers/kumar-2023-certifying-llm-safety-against-adversarial/) — Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al. · 2023 - [Character-LLM: A Trainable Agent for Role-Playing](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/) — Yunfan Shao, Linyang Li, Junqi Dai, et al. · 2023 - [ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge](https://md.research.elamur.ai/free/en/papers/li-2023-chatdoctor-medical-chat-model-fine/) — Yunxiang Li, Zihan Li, Kai Zhang, et al. · 2023 - [ChatGPT as a Factual Inconsistency Evaluator for Text Summarization](https://md.research.elamur.ai/free/en/papers/luo-2023-chatgpt-factual-inconsistency-evaluator-text/) — Zheheng Luo, Qianqian Xie, Sophia Ananiadou · 2023 - [ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) — Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al. · 2023 - [ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/) — Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al. · 2023 - [ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer](https://md.research.elamur.ai/free/en/papers/liu-2023-chatgpt-vs-human-authored-text/) — Dongqi Liu, Vera Demberg · 2023 - [ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning](https://md.research.elamur.ai/free/en/papers/tornberg-2023-chatgpt-4-outperforms-experts-crowd/) — Petter Tornberg · 2023 - [ChatGPT: Jack of all trades, master of none](https://md.research.elamur.ai/free/en/papers/kocon-2023-chatgpt-jack-all-trades-master/) — Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al. · 2023 - [Chinese Idiom Paraphrasing](https://md.research.elamur.ai/free/en/papers/qiang-2023-chinese-idiom-paraphrasing/) — Jipeng Qiang, Yang Li, Chaowei Zhang, et al. · 2023 - [CogAgent: A Visual Language Model for GUI Agents](https://md.research.elamur.ai/free/en/papers/hong-2023-cogagent-visual-language-model/) — Wenyi Hong, Weihan Wang, Qingsong Lv, et al. · 2023 - [CogVLM: Visual Expert for Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/) — Weihan Wang, Qingsong Lv, Wenmeng Yu, et al. · 2023 - [Compressing Context to Enhance Inference Efficiency of Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-compressing-context-enhance-inference-efficiency/) — Yucheng Li, Bo Dong, Frank Guerin, et al. · 2023 - [Context-faithful Prompting for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/) — Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al. · 2023 - [Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/) — Libo Qin, Qiguang Chen, Fuxuan Wei, et al. · 2023 - [Culturally Aware Natural Language Inference](https://md.research.elamur.ai/free/en/papers/huang-2023-culturally-aware-natural-language-inference/) — Jing Huang, Diyi Yang · 2023 - [DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/) — Yanchen Liu, William Held, Diyi Yang · 2023 - [DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) — Boxin Wang, Weixin Chen, Hengzhi Pei, et al. · 2023 - [Dependency Dialogue Acts — Annotation Scheme and Case Study](https://md.research.elamur.ai/free/en/papers/cai-2023-dependency-dialogue-acts-annotation-scheme/) — Jon Z. Cai, Brendan King, Margaret Perkoff, et al. · 2023 - [DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature](https://md.research.elamur.ai/free/en/papers/mitchell-2023-detectgpt-zero-shot-machine-generated/) — Eric Mitchell, Yoonho Lee, Alexander Khazatsky, et al. · 2023 [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [16](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) **17** [18](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/)