--- title: "Natural language processing — papers, page 20" description: "Natural language processing: 2421 papers of the Elamur Research library · page 20 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/20/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/20/) [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 20 # 💬 Natural language processing 2421 papers · page 20 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/19/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [19](https://md.research.elamur.ai/free/en/shelves/nlp/page/19/) **20** [21](https://md.research.elamur.ai/free/en/shelves/nlp/page/21/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/21/) - [LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain](https://md.research.elamur.ai/free/en/papers/niklaus-2023-lextreme-multi-lingual-multi-task/) — Joel Niklaus, Veton Matoshi, Pooja Rani, et al. · 2023 - [Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/) — Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al. · 2023 - [LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/) — Zhiqiang Hu, Lei Wang, Yihuai Lan, et al. · 2023 - [LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/) — Dongfu Jiang, Xiang Ren, Bill Yuchen Lin · 2023 - [LLM-Pruner: On the Structural Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-llm-pruner-structural-pruning-large/) — Xinyin Ma, Gongfan Fang, Xinchao Wang · 2023 - [LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/) — Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al. · 2023 - [Locally Typical Sampling](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/) — Clara Meister, Tiago Pimentel, Gian Wiher, et al. · 2023 - [LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding](https://md.research.elamur.ai/free/en/papers/bai-2023-longbench-bilingual-multitask-benchmark/) — Yushi Bai, Xin Lv, Jiajie Zhang, et al. · 2023 - [LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization](https://md.research.elamur.ai/free/en/papers/krishna-2023-longeval-guidelines-human-evaluation-faithfulness/) — Kalpesh Krishna, Erin Bransom, Bailey Kuehl, et al. · 2023 - [Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-looking-needle-haystack-comprehensive-study/) — Nuno M. Guerreiro, Elena Voita, André Martins · 2023 - [Machine Learning for Ancient Languages: A Survey](https://md.research.elamur.ai/free/en/papers/sommerschield-2023-machine-learning-ancient-languages-survey/) — Thea Sommerschield, Yannis Assael, John Pavlopoulos, et al. · 2023 - [Making Retrieval-Augmented Language Models Robust to Irrelevant Context](https://md.research.elamur.ai/free/en/papers/yoran-2023-making-retrieval-augmented-language-models/) — Ori Yoran, Tomer Wolfson, Ori Ram, et al. · 2023 - [Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2023-marked-personas-natural-language-prompts/) — Myra Cheng, Esin Durmus, Dan Jurafsky · 2023 - [MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods](https://md.research.elamur.ai/free/en/papers/finkelstein-2023-mbr-qe-finetuning-training-time/) — Mara Finkelstein; Subhajit Naskar; Mehdi Mirzazadeh; Apurva Shah;, Markus Freitag · 2023 - [Measuring Attribution in Natural Language Generation Models](https://md.research.elamur.ai/free/en/papers/rashkin-2023-measuring-attribution-natural-language-generation/) — Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, et al. · 2023 - [Med-HALT: Medical Domain Hallucination Test for Large Language Models](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/) — Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu · 2023 - [MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data](https://md.research.elamur.ai/free/en/papers/han-2023-medalpaca-open-source-collection-medical/) — Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, et al. · 2023 - [MEDITRON-70B: Scaling Medical Pretraining for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/) — Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al. · 2023 - [MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/) — Xingyao Wang, Zihan Wang, Jiateng Liu, et al. · 2023 - [Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/) — Suyu Ge, Yunan Zhang, Liyuan Liu, et al. · 2023 - [mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl2-revolutionizing-multi-modal/) — Qinghao Ye, Haiyang Xu, Jiabo Ye, et al. · 2023 - [mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl-modularization-empowers-large/) — Qinghao Ye, Haiyang Xu, Guohai Xu, et al. · 2023 - [Multi-step Jailbreaking Privacy Attacks on ChatGPT](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/) — Haoran Li, Dadi Guo, Wei Fan, et al. · 2023 - [Multi-VALUE: A Framework for Cross-Dialectal English NLP](https://md.research.elamur.ai/free/en/papers/ziems-2023-multi-value-framework-cross-dialectal/) — Caleb Ziems, William Held, Jingfeng Yang, et al. · 2023 - [Multilingual Sequence-to-Sequence Models for Hebrew NLP](https://md.research.elamur.ai/free/en/papers/findings-2023-eyal-multilingual-sequence-sequence-models-hebrew/) — Matan Eyal, Hila Noga, Roee Aharoni, et al. · 2023 [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/19/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [19](https://md.research.elamur.ai/free/en/shelves/nlp/page/19/) **20** [21](https://md.research.elamur.ai/free/en/shelves/nlp/page/21/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/21/)