--- title: "Natural language processing — papers, page 19" description: "Natural language processing: 2421 papers of the Elamur Research library · page 19 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/19/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/19/) [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 19 # 💬 Natural language processing 2421 papers · page 19 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/18/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [18](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) **19** [20](https://md.research.elamur.ai/free/en/shelves/nlp/page/20/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/20/) - [GlotLID: Language Identification for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/kargaran-2023-glotlid-language-identification-low-resource/) — Amir Hossein Kargaran, Ayyoob Imani, François Yvon, et al. · 2023 - [GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/) — Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al. · 2023 - [GPT-RE: In-context Learning for Relation Extraction using Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/) — Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al. · 2023 - [GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models](https://md.research.elamur.ai/free/en/papers/prasad-2023-grips-gradient-free-edit-based/) — Archiki Prasad, Peter Hase, Xiang Zhou, et al. · 2023 - [Hallucinations in Large Multilingual Translation Models](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/) — Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al. · 2023 - [HeGeL: A Novel Dataset for Geo-Location from Hebrew Text](https://md.research.elamur.ai/free/en/papers/findings-2023-argaman-hegel-novel-dataset-geo-location/) — Tzuf Paz-Argaman, Tal Bauman, Itai Mondshine, et al. · 2023 - [HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark](https://md.research.elamur.ai/free/en/papers/findings-2023-cohen-heq-large-diverse-hebrew-reading/) — Amir DN Cohen, Hilla Merhav, Yoav Goldberg, et al. · 2023 - [Hexatagging: Projective Dependency Parsing as Tagging](https://md.research.elamur.ai/free/en/papers/acl-2023-amini-hexatagging-projective-dependency-parsing-as/) — Afra Amini, Tianyu Liu, Ryan Cotterell · 2023 - [HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2023-huatuo-tuning-llama-model-chinese/) — Haochun Wang, Chi Liu, Nuwa Xi, et al. · 2023 - [HuatuoGPT, Towards Taming Language Model to Be a Doctor](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/) — Hongbo Zhang, Junying Chen, Feng Jiang, et al. · 2023 - [Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing](https://md.research.elamur.ai/free/en/papers/jung-2023-impossible-distillation-low-quality-model/) — Jaehun Jung, Peter West, Liwei Jiang, et al. · 2023 - [Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/) — Yao Fu, Hao Peng, Tushar Khot, et al. · 2023 - [Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/siriwardhana-2023-improving-domain-adaptation-retrieval-augmented/) — Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, et al. · 2023 - [In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) — Sweta Agrawal, Chunting Zhou, Mike Lewis, et al. · 2023 - [In-Context Learning Creates Task Vectors](https://md.research.elamur.ai/free/en/papers/hendel-2023-context-learning-creates-task-vectors/) — Roee Hendel, Mor Geva, Amir Globerson · 2023 - [INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback](https://md.research.elamur.ai/free/en/papers/xu-2023-instructscore-explainable-text-generation-evaluation/) — Wenda Xu, Danqing Wang, Liangming Pan, et al. · 2023 - [InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/) — Zhe Chen, Jiannan Wu, Wenhai Wang, et al. · 2023 - [Large Language Model Alignment: A Survey](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/) — Tianhao Shen, Renren Jin, Yufei Huang, et al. · 2023 - [Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) — Yubo Ma, Yixin Cao, Yong Hong, et al. · 2023 - [Large Language Models are few(1)-shot Table Reasoners](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/) — Wenhu Chen · 2023 - [Large Language Models Can Self-Improve](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/) — Jiaxin Huang, Shixiang Gu, Le Hou, et al. · 2023 - [Large Language Models with Controllable Working Memory](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-controllable-working/) — Daliang Li, Ankit Singh Rawat, Manzil Zaheer, et al. · 2023 - [Larger language models do in-context learning differently](https://md.research.elamur.ai/free/en/papers/wei-2023-larger-language-models-context-learning/) — Jerry Wei, Jason Wei, Yi Tay, et al. · 2023 - [LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/) — Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li · 2023 - [LENS: A Learnable Evaluation Metric for Text Simplification](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/) — Mounica Maddela, Yao Dou, David Heineman, et al. · 2023 [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [18](https://md.research.elamur.ai/free/en/shelves/nlp/page/18/) **19** [20](https://md.research.elamur.ai/free/en/shelves/nlp/page/20/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/20/)