--- title: "Papers of 2022 — page 2" description: "Papers of 2022: 455 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/papers/2022/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2022/page/2/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2022 # Papers of 2022 — page 2 455 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2022/) [1](https://md.research.elamur.ai/free/en/papers/2022/) **2** [3](https://md.research.elamur.ai/free/en/papers/2022/page/3/) [4](https://md.research.elamur.ai/free/en/papers/2022/page/4/) [5](https://md.research.elamur.ai/free/en/papers/2022/page/5/) [next →](https://md.research.elamur.ai/free/en/papers/2022/page/3/) - [Crosslingual Generalization through Multitask Finetuning](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/) — Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al. · arXiv:2211.01786 - [CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic](https://md.research.elamur.ai/free/en/papers/mahdaouy-2022-cs-um6p-semeval-2022-task/) — Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, et al. · Proceedings of the 16th International Workshop… - [CSECU-DSG @ Causal News Corpus 2022: Fusion of RoBERTa Transformers Variants for Causal Event Classification](https://md.research.elamur.ai/free/en/papers/aziz-2022-csecu-dsg-causal-news-corpus/) — Abdul Aziz, Md. Akram Hossain, Abu Nowshed Chy · Proceedings of the 5th Workshop on Challenges… - [CTRLsum: Towards Generic Controllable Text Summarization](https://md.research.elamur.ai/free/en/papers/he-2022-ctrlsum-generic-controllable-text-summarization/) — Junxian He, Wojciech Kryscinski, Bryan McCann, et al. · Proceedings of the 2022 Conference on Empirical… - [Current Trends and Approaches in Synonyms Extraction: Potential Adaptation to Arabic](https://md.research.elamur.ai/free/en/papers/naser-2022-karajah-current-trends-approaches-synonyms-extraction/) — Eman Naser-Karajah, Nabil Arman, Mustafa Jarrar · arXiv:2205.10412 · In Proceedings of the 11th… - [Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models](https://md.research.elamur.ai/free/en/papers/iv-2022-cutting-down-prompts-parameters-simple/) — Robert Logan IV, Ivana Balazevic, Eric Wallace, et al. · Findings of the Association for Computational… - [Dartmouth at SemEval-2022 Task 6: Detection of Sarcasm](https://md.research.elamur.ai/free/en/papers/lad-2022-dartmouth-semeval-2022-task-6/) — Rishik Lad, Weicheng Ma, Soroush Vosoughi · Proceedings of the 16th International Workshop… - [Data Augmentation using Transformers and Similarity Measures for Improving Arabic Text Classification](https://md.research.elamur.ai/free/en/papers/refai-2022-data-augmentation-using-transformers-similarity/) — Dania Refai, Saleh Abo-Soud, Mohammad Abdel-Rahman · arXiv:2212.13939 - [Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations](https://md.research.elamur.ai/free/en/papers/davani-2022-dealing-disagreements-looking-beyond-majority/) — Aida Mostafazadeh Davani, Mark Díaz, Vinodkumar Prabhakaran · Transactions of the Association for… - [Deduplicating Training Data Mitigates Privacy Risks in Language Models](https://md.research.elamur.ai/free/en/papers/kandpal-2022-deduplicating-training-data-mitigates-privacy/) — Nikhil Kandpal, Eric Wallace, Colin Raffel · arXiv:2202.06539 - [Deep Multi-Task Models for Misogyny Identification and Categorization on Arabic Social Media](https://md.research.elamur.ai/free/en/papers/mahdaouy-2022-deep-multi-task-models-misogyny/) — Abdelkader El Mahdaouy, Abdellah El Mekki, Ahmed Oumar, et al. · arXiv:2206.08407 - [DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale](https://md.research.elamur.ai/free/en/papers/rajbhandari-2022-deepspeed-moe-advancing-mixture-experts/) — Samyam Rajbhandari, Conglong Li, Zhewei Yao, et al. · arXiv:2201.05596 - [DEGREE: A Data-Efficient Generation-Based Event Extraction Model](https://md.research.elamur.ai/free/en/papers/hsu-2022-degree-data-efficient-generation-based/) — I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, et al. · Proceedings of the 2022 Conference of the North… - [Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/) — Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al. · arXiv:2212.14024 - [Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training](https://md.research.elamur.ai/free/en/papers/scholman-2022-design-choices-crowdsourcing-discourse-relation/) — Merel Scholman, Valentina Pyatkin, Frances Yung, et al. · Proceedings of the Thirteenth Language… - [Detection of Negative Campaign in Israeli Municipal Elections](https://md.research.elamur.ai/free/en/papers/aclbulk-2022-litvak-detection-negative-campaign-israeli-municipal/) — Marina Litvak, Natalia Vanetik, Sagiv Talker, et al. · Modern Hebrew - [DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/chuang-2022-diffcse-difference-based-contrastive-learning/) — Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, et al. · Proceedings of the 2022 Conference of the North… - [Diffusion-LM Improves Controllable Text Generation](https://md.research.elamur.ai/free/en/papers/li-2022-diffusion-lm-improves-controllable-text/) — Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, et al. · arXiv:2205.14217 - [DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations](https://md.research.elamur.ai/free/en/papers/scholman-2022-discogem-crowdsourced-corpus-genre-mixed/) — Merel Scholman, Tianai Dong, Frances Yung, et al. · English - [Discovering Language Model Behaviors with Model-Written Evaluations](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/) — Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al. · arXiv:2212.09251 - [Disentangling Indirect Answers to Yes-No Questions in Real Conversations](https://md.research.elamur.ai/free/en/papers/sanagavarapu-2022-disentangling-indirect-answers-yes-no/) — Krishna Sanagavarapu, Jathin Singaraju, Anusha Kakileti, et al. · English - [Do As I Can, Not As I Say: Grounding Language in Robotic Affordances](https://md.research.elamur.ai/free/en/papers/ahn-2022-i-i-say-grounding-language/) — Michael Ahn, Anthony Brohan, Noah Brown, et al. · arXiv:2204.01691 - [Do Bashal and Hepsō really mean 'boil'? A preliminary study in the semantics of biblical Hebrew and Septuagint Greek](https://md.research.elamur.ai/free/en/papers/hbo-2022-mangum-bashal-hepso-really-mean-boil/) — Douglas T. Mangum · Ancient Hebrew - [Do Prompt-Based Models Really Understand the Meaning of Their Prompts?](https://md.research.elamur.ai/free/en/papers/webson-2022-do-prompt-based-models-really/) — Albert Webson, Ellie Pavlick · Proceedings of the 2022 Conference of the North… - [DocAMR: Multi-Sentence AMR Representation and Evaluation](https://md.research.elamur.ai/free/en/papers/naseem-2022-docamr-multi-sentence-amr-representation/) — Tahira Naseem, Austin Blodgett, Sadhana Kumaravel, et al. · Machine translation - [Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/) — Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al. · arXiv:2210.12283 - [Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2022-dynamic-prompt-learning-policy-gradient/) — Pan Lu, Liang Qiu, Kai-Wei Chang, et al. · arXiv:2209.14610 - [Editing Models with Task Arithmetic](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/) — Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al. · arXiv:2212.04089 - [Efficient Training of Language Models to Fill in the Middle](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/) — Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al. · arXiv:2207.14255 - [Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://md.research.elamur.ai/free/en/papers/vernikos-2022-embarrassingly-easy-document-level-mt/) — Giorgos Vernikos, Brian Thompson, Prashant Mathur, et al. · Proceedings of the Seventh Conference on… - [Emergent Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/) — Jason Wei, Yi Tay, Rishi Bommasani, et al. · arXiv:2206.07682 - [Emojis as Anchors to Detect Arabic Offensive Language and Hate Speech](https://md.research.elamur.ai/free/en/papers/mubarak-2022-emojis-anchors-detect-arabic-offensive/) — Hamdy Mubarak, Sabit Hassan, Shammur Absar Chowdhury · arXiv:2201.06723 - [Encoding and Fusing Semantic Connection and Linguistic Evidence for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/xiang-2022-encoding-fusing-semantic-connection-linguistic/) — Wei Xiang, Bang Wang, Lu Dai, et al. · Findings of the Association for Computational… - [End-to-end Multilingual Coreference Resolution with Mention Head Prediction](https://md.research.elamur.ai/free/en/papers/prazak-2022-end-end-multilingual-coreference-resolution/) — Ondřej Pražák, Miloslav Konopik · Proceedings of the CRAC 2022 Shared Task on… - [Epistemic Modality in Amharic](https://md.research.elamur.ai/free/en/papers/krzyzanowska-2022-epistemic-modality-amharic/) — Magdalena Krzyzanowska · Aethiopica 24 - [Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks](https://md.research.elamur.ai/free/en/papers/asai-2022-evidentiality-guided-generation-knowledge-intensive/) — Akari Asai, Matt Gardner, Hannaneh Hajishirzi · Proceedings of the 2022 Conference of the North… - [ExaASC: A General Target-Based Stance Detection Corpus in Arabic Language](https://md.research.elamur.ai/free/en/papers/jaziriyan-2022-exaasc-general-target-based-stance/) — Mohammad Mehdi Jaziriyan, Ahmad Akbari, Hamed Karbasi · arXiv:2204.13979 · 2021 11th International… - [Explanation and interpretation of three unclear words in Bavli Eruvin 104a-b](https://md.research.elamur.ai/free/en/papers/zur-2022-explanation-interpretation-three-unclear-words/) — Uri Zur · HTS Teologiese Studies/Theological Studies 78 - [Exploiting Sentiment and Common Sense for Zero-shot Stance Detection](https://md.research.elamur.ai/free/en/papers/luo-2022-exploiting-sentiment-common-sense-zero/) — Yun Luo, Zihan Liu, Yuefeng Shi, et al. · Proceedings of the 29th International… - [Exploring Length Generalization in Large Language Models](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/) — Cem Anil, Yuhuai Wu, Anders Andreassen, et al. · arXiv:2207.04901 - [Extracting Latent Steering Vectors from Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/) — Nishant Subramani, Nivedita Suresh, Matthew Peters · Findings of the Association for Computational… - [F-coref: Fast, Accurate and Easy to Use Coreference Resolution](https://md.research.elamur.ai/free/en/papers/otmazgin-2022-f-coref-fast-accurate-easy/) — Shon Otmazgin, Arie Cattan, Yoav Goldberg · Proceedings of the 2nd Conference of the… - [Facilitating Contrastive Learning of Discourse Relational Senses by Exploiting the Hierarchy of Sense Relations](https://md.research.elamur.ai/free/en/papers/long-2022-facilitating-contrastive-learning-discourse-relational/) — Wanqiu Long, Bonnie Webber · Proceedings of the 2022 Conference on Empirical… - [Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension](https://md.research.elamur.ai/free/en/papers/xu-2022-fantastic-questions-where-find-them/) — Ying Xu, Dakuo Wang, Mo Yu, et al. · Mova's core list - [Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity](https://md.research.elamur.ai/free/en/papers/lu-2022-fantastically-ordered-prompts-where-find/) — Yao Lu, Max Bartolo, Alastair Moore, et al. · Proceedings of the 60th Annual Meeting of the… - [FeTaQA: Free-form Table Question Answering](https://md.research.elamur.ai/free/en/papers/nan-2022-fetaqa-free-form-table-question/) — Linyong Nan, Chiachun Hsieh, Ziming Mao, et al. · Transactions of the Association for… - [Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Experts](https://md.research.elamur.ai/free/en/papers/le-2022-few-shot-anaphora-resolution-scientific/) — Nghia T. Le, Fan Bai, Alan Ritter · Findings of the Association for Computational… - [Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/) — Haokun Liu, Derek Tam, Mohammed Muqeeth, et al. · arXiv:2205.05638 - [Few-Shot Self-Rationalization with Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/) — Ana Marasovic, Iz Beltagy, Doug Downey, et al. · Findings of the Association for Computational… - [FII UAIC at SemEval-2022 Task 6: iSarcasmEval - Intended Sarcasm Detection in English and Arabic](https://md.research.elamur.ai/free/en/papers/manoleasa-2022-fii-uaic-semeval-2022-task/) — Tudor Manoleasa, Daniela Gifu, Iustin Sandu · Proceedings of the 16th International Workshop… - [Findings of the IWSLT 2022 Evaluation Campaign](https://md.research.elamur.ai/free/en/papers/anastasopoulos-2022-findings-iwslt-2022-evaluation-campaign/) — Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, et al. · Proceedings of the 19th International… - [Findings of the WMT 2022 Shared Task on Quality Estimation](https://md.research.elamur.ai/free/en/papers/zerva-2022-findings-wmt-2022-shared-task/) — Chrysoula Zerva, Frédéric Blain, Ricardo Rei, et al. · Proceedings of the Seventh Conference on… - [Fine-Tuning Approach for Arabic Offensive Language Detection System: BERT-Based Model](https://md.research.elamur.ai/free/en/papers/husain-2022-fine-tuning-approach-arabic-offensive/) — Fatemah Husain, Ozlem Uzuner · arXiv:2203.03542 - [Flamingo: a Visual Language Model for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/) — Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al. · arXiv:2204.14198 - [FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech](https://md.research.elamur.ai/free/en/papers/conneau-2022-fleurs-few-shot-learning-evaluation/) — Alexis Conneau, Min Ma, Simran Khanuja, et al. · arXiv:2205.12446 - [Flow Matching for Generative Modeling](https://md.research.elamur.ai/free/en/papers/lipman-2022-flow-matching-generative-modeling/) — Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, et al. · arXiv:2210.02747 - [Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/) — Xingchao Liu, Chengyue Gong, Qiang Liu · arXiv:2209.03003 - [FLUTE: Figurative Language Understanding through Textual Explanations](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/) — Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al. · Proceedings of the 2022 Conference on Empirical… - [FNet: Mixing Tokens with Fourier Transforms](https://md.research.elamur.ai/free/en/papers/thorp-2022-fnet-mixing-tokens-fourier-transforms/) — James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, et al. · Proceedings of the 2022 Conference of the North… - [FOLIO: Natural Language Reasoning with First-Order Logic](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/) — Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al. · arXiv:2209.00840 - [Formal Mathematics Statement Curriculum Learning](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/) — Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al. · arXiv:2202.01344 - [French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English](https://md.research.elamur.ai/free/en/papers/neveol-2022-french-crows-pairs-extending-challenge/) — Aurélie Névéol, Yoann Dupont, Julien Bezançon, et al. · Proceedings of the 60th Annual Meeting of the… - [From Pattern to Interpretation. Using Colibri Core to Detect Translation Patterns in the Peshitta.](https://md.research.elamur.ai/free/en/papers/lingbulk-2022-coeckelbergs-pattern-interpretation-colibri-core-detect/) — Mathias Coeckelbergs · Aramaic - [Galactica: A Large Language Model for Science](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/) — Ross Taylor, Marcin Kardas, Guillem Cucurull, et al. · arXiv:2211.09085 - [GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing](https://md.research.elamur.ai/free/en/papers/peng-2022-gcdt-chinese-rst-treebank-multigenre/) — Siyao Peng, Yang Janet Liu, Amir Zeldes · Proceedings of the 2nd Conference of the… - [GeezSwitch: Language Identification in Typologically Related Low-resourced East African Languages](https://md.research.elamur.ai/free/en/papers/gaim-2022-geezswitch-language-identification-typologically-related/) — Fitsum Gaim, Wonsuk Yang, Jong C. Park · Proceedings of the Thirteenth Language… - [Genealogy of the Root of "Katb" (ک ت ب) in Semitic Languages, with an Analysis of its Meaning in the Qur'an and the Bible](https://md.research.elamur.ai/free/en/papers/hemati-2022-genealogy-root-katb-semitic-languages/) — mohammadali hemati, Mohammad Kazem Shaker · پژوهش نامه معارف قرآنی 13 - [Generate rather than Retrieve: Large Language Models are Strong Context Generators](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/) — Wenhao Yu, Dan Iter, Shuohang Wang, et al. · arXiv:2209.10063 - [Generating Sequences by Learning to Self-Correct](https://md.research.elamur.ai/free/en/papers/welleck-2022-generating-sequences-learning-self-correct/) — Sean Welleck, Ximing Lu, Peter West, et al. · arXiv:2211.00053 - [Generating Training Data with Language Models: Towards Zero-Shot Language Understanding](https://md.research.elamur.ai/free/en/papers/meng-2022-generating-training-data-language-models/) — Yu Meng, Jiaxin Huang, Yu Zhang, et al. · arXiv:2202.04538 - [Generative Data Augmentation with Contrastive Learning for Zero-Shot Stance Detection](https://md.research.elamur.ai/free/en/papers/li-2022-generative-data-augmentation-contrastive-learning/) — Yang Li, Jiawei Yuan · Proceedings of the 2022 Conference on Empirical… - [GLM-130B: An Open Bilingual Pre-trained Model](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/) — Aohan Zeng, Xiao Liu, Zhengxiao Du, et al. · arXiv:2210.02414 - [GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/) — Zhengxiao Du, Yujie Qian, Xiao Liu, et al. · Proceedings of the 60th Annual Meeting of the… - [GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2022-gpl-generative-pseudo-labeling-unsupervised/) — Kexin Wang, Nandan Thakur, Nils Reimers, et al. · Proceedings of the 2022 Conference of the North… - [GPT-NeoX-20B: An Open-Source Autoregressive Language Model](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/) — Sidney Black, Stella Biderman, Eric Hallahan, et al. · Proceedings of BigScience Episode \#5 –… - [Graph Pre-training for AMR Parsing and Generation](https://md.research.elamur.ai/free/en/papers/bai-2022-graph-pre-training-amr-parsing/) — Xuefeng Bai, Yulong Chen, Yue Zhang · Proceedings of the 60th Annual Meeting of the… - [GRAVL-BERT: Graphical Visual-Linguistic Representations for Multimodal Coreference Resolution](https://md.research.elamur.ai/free/en/papers/guo-2022-gravl-bert-graphical-visual-linguistic/) — Danfeng Guo, Arpit Gupta, Sanchit Agarwal, et al. · Proceedings of the 29th International… - [GuoFeng: A Benchmark for Zero Pronoun Recovery and Translation](https://md.research.elamur.ai/free/en/papers/xu-2022-guofeng-benchmark-zero-pronoun-recovery/) — Mingzhou Xu, Longyue Wang, Derek F. Wong, et al. · Proceedings of the 2022 Conference on Empirical… - [Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2022-hallucinated-but-factual-inspecting-factuality/) — Meng Cao, Yue Dong, Jackie Cheung · Proceedings of the 60th Annual Meeting of the… - [Handling Stress in Finite-State Morphological Analyzers for Ancient Greek and Ancient Hebrew](https://md.research.elamur.ai/free/en/papers/aclbulk-2022-swanson-handling-stress-finite-state-morphological/) — Daniel G. Swanson, Francis M. Tyers · Ancient Hebrew - [Harnessing Multilingual Resources to Question Answering in Arabic](https://md.research.elamur.ai/free/en/papers/alnajjar-2022-harnessing-multilingual-resources-question-answering/) — Khalid Alnajjar, Mika Hamalainen · arXiv:2205.08024 - [Hebrew nominals do not require functional structure above the NP](https://md.research.elamur.ai/free/en/papers/lingbulk-2022-bruening-hebrew-nominals-do-not-require/) — Benjamin Bruening · Modern Hebrew - [Hierarchical Aggregation of Dialectal Data for Arabic Dialect Identification](https://md.research.elamur.ai/free/en/papers/baimukan-2022-hierarchical-aggregation-dialectal-data-arabic/) — Nurpeiis Baimukan, Houda Bouamor, Nizar Habash · Proceedings of the Thirteenth Language… - [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://md.research.elamur.ai/free/en/papers/ramesh-2022-hierarchical-text-conditional-image-generation/) — Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, et al. · arXiv:2204.06125 - [High Fidelity Neural Audio Compression](https://md.research.elamur.ai/free/en/papers/defossez-2022-high-fidelity-neural-audio-compression/) — Alexandre Defossez, Jade Copet, Gabriel Synnaeve, et al. · arXiv:2210.13438 - [High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics](https://md.research.elamur.ai/free/en/papers/freitag-2022-high-quality-rather-than-high/) — Markus Freitag, David Grangier, Qijun Tan, et al. · Transactions of the Association for… - [High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts](https://md.research.elamur.ai/free/en/papers/alami-2022-high-tech-team-semeval-2022/) — Hamza Alami, Abdessamad Benlahbib, Ahmed Alami · Proceedings of the 16th International Workshop… - [How do we get there? Evaluating transformer neural networks as cognitive models for English past tense inflection](https://md.research.elamur.ai/free/en/papers/ma-2022-how-do-we-get-there/) — Xiaomeng Ma, Lingyu Gao · English - [How Much Does Lookahead Matter for Disambiguation? 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