{"id":114,"date":"2023-01-25T03:02:39","date_gmt":"2023-01-25T03:02:39","guid":{"rendered":"https:\/\/todaysainews.com\/index.php\/2023\/01\/25\/google-at-emnlp-2022-google-ai-blog\/"},"modified":"2025-04-27T07:36:12","modified_gmt":"2025-04-27T07:36:12","slug":"google-at-emnlp-2022-google-ai-blog","status":"publish","type":"post","link":"https:\/\/todaysainews.com\/index.php\/2023\/01\/25\/google-at-emnlp-2022-google-ai-blog\/","title":{"rendered":"Google at EMNLP 2022 \u2013 Google AI Blog"},"content":{"rendered":"

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\n<\/p>\n

\nPosted by Malaya Jules, Program Manager, Google<\/span><\/p>\n

\"EMNLP<\/p>\n

\nThis week, the premier conference on Empirical Methods in Natural Language Processing<\/a> (EMNLP 2022) is being held in Abu Dhabi, United Arab Emirates. We are proud to be a Diamond Sponsor<\/a> of EMNLP 2022, with Google researchers contributing at all levels. This year we are presenting over 50 papers and are actively involved in 10 different workshops and tutorials.<\/p>\n

<\/p>\n

\nIf you\u2019re registered for EMNLP 2022, we hope you\u2019ll visit the Google booth to learn more about the exciting work across various topics, including language interactions, causal inference, question answering and more. Take a look below to learn more about the Google research being presented at EMNLP 2022 (Google affiliations in bold<\/strong>).\n<\/p>\n

Committees<\/h2>\n

\nOrganizing Committee includes: Eunsol Choi<\/em><\/strong>, Imed Zitouni<\/em><\/strong>\n<\/p>\n

\nSenior Program Committee includes: Don Metzler<\/em><\/strong>, Eunsol Choi<\/em><\/strong>, Bernd Bohnet<\/em><\/strong>, Slav Petrov<\/em><\/strong>, Kenthon Lee<\/em><\/strong>\n<\/p>\n

Papers<\/h2>\n

\nTransforming Sequence Tagging Into A Seq2Seq Task<\/a>
\n
Karthik Raman<\/b>, Iftekhar Naim<\/b>, Jiecao Chen<\/b>, Kazuma Hashimoto<\/b>, Kiran Yalasangi<\/b>, Krishna Srinivasan<\/b><\/em>\n<\/p>\n

\nOn the Limitations of Reference-Free Evaluations of Generated Text<\/a>
\n
Daniel Deutsch<\/b>, Rotem Dror<\/b>, Dan Roth<\/b><\/em>\n<\/p>\n

\nChunk-Based Nearest Neighbor Machine Translation<\/a>
\n
Pedro Henrique Martins, Zita Marinho<\/strong>, Andr\u00e9 F. T. Martins<\/em>\n<\/p>\n

\nEvaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing<\/a>
\n
Linlu Qiu*, Peter Shaw<\/strong>, Panupong Pasupat<\/strong>, Tianze Shi<\/strong>, Jonathan Herzig<\/strong>, Emily Pitler<\/strong>, Fei Sha<\/strong>, Kristina Toutanova<\/strong><\/em>\n<\/p>\n

\nMasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition<\/a>
\n
David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder<\/strong>, Shruti Rijhwani, Michael Beukman, Chester Palen-Michel, Constantine Lignos, Jesujoba O. Alabi, Shamsuddeen H. Muhammad, Peter Nabende, Cheikh M. Bamba Dione, Andiswa Bukula, Rooweither Mabuya, Bonaventure F. P. Dossou, Blessing Sibanda, Happy Buzaaba, Jonathan Mukiibi, Godson Kalipe, Derguene Mbaye, Amelia Taylor, Fatoumata Kabore, Chris Chinenye Emezue, Anuoluwapo Aremu, Perez Ogayo, Catherine Gitau, Edwin Munkoh-Buabeng, Victoire M. Koagne, Allahsera Auguste Tapo, Tebogo Macucwa, Vukosi Marivate, Elvis Mboning, Tajuddeen Gwadabe, Tosin Adewumi, Orevaoghene Ahia, Joyce Nakatumba-Nabende, Neo L. Mokono, Ignatius Ezeani, Chiamaka Chukwuneke, Mofetoluwa Adeyemi, Gilles Q. Hacheme, Idris Abdulmumin, Odunayo Ogundepo, Oreen Yousuf, Tatiana Moteu Ngoli, Dietrich Klakow<\/em>\n<\/p>\n

\nT-STAR: Truthful Style Transfer Using AMR Graph as Intermediate Representation<\/a>
\n
Anubhav Jangra<\/b>, Preksha Nema<\/b>, Aravindan Raghuveer<\/b><\/em>\n<\/p>\n

\nExploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature<\/a>
\n
Katherine Thai, Marzena Karpinska, Kalpesh Krishna, Bill Ray, Moira Inghilleri, John Wieting<\/strong>, Mohit Iyyer<\/em>\n<\/p>\n

\nASQA: Factoid Questions Meet Long-Form Answers<\/a>
\n
Ivan Stelmakh*, Yi Luan<\/strong>, Bhuwan Dhingra<\/strong>, Ming-Wei Chang<\/strong><\/em>\n<\/p>\n

\nEfficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization<\/a>
\n
Nishant Yadav, Nicholas Monath<\/strong>, Rico Angell, Manzil Zaheer<\/strong>, Andrew McCallum<\/em>\n<\/p>\n

\nCPL: Counterfactual Prompt Learning for Vision and Language Models<\/a>
\n
Xuehai He, Diji Yang, Weixi Feng, Tsu-Jui Fu, Arjun Akula<\/strong>, Varun Jampani<\/strong>, Pradyumna Narayana<\/strong>, Sugato Basu<\/strong>, William Yang Wang, Xin Eric Wang<\/em>\n<\/p>\n

\nCorrecting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling<\/a>
\n
Vidhisha Balachandran, Hannaneh Hajishirzi, William Cohen<\/strong>, Yulia Tsvetkov<\/em>\n<\/p>\n

\nDungeons and Dragons as a Dialog Challenge for Artificial Intelligence<\/a>
\n
Chris Callison-Burch, Gaurav Singh Tomar<\/strong>, Lara J Martin, Daphne Ippolito<\/strong>, Suma Bailis<\/strong>, David Reitter<\/strong><\/em>\n<\/p>\n

\nExploring Dual Encoder Architectures for Question Answering<\/a>
\n
Zhe Dong<\/strong>, Jianmo Ni<\/strong>, Daniel M. Bikel<\/strong>, Enrique Alfonseca<\/strong>, Yuan Wang<\/strong>, Chen Qu<\/strong>, Imed Zitouni<\/strong>\n<\/p>\n

\nRED-ACE: Robust Error Detection for ASR Using Confidence Embeddings<\/a>
\n
Zorik Gekhman<\/b>, Dina Zverinski<\/b>, Jonathan Mallinson<\/b>, Genady Beryozkin<\/b><\/em>\n<\/p>\n

\nImproving Passage Retrieval with Zero-Shot Question Generation<\/a>
\n
Devendra Sachan, Mike Lewis, Mandar Joshi<\/strong>, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer<\/em>\n<\/p>\n

\nMuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering Over Images and Text<\/a>
\n
Wenhu Chen<\/b>, Hexiang Hu<\/b>, Xi Chen<\/b>, Pat Verga<\/b>, William Cohen<\/b><\/em>\n<\/p>\n

\nDecoding a Neural Retriever’s Latent Space for Query Suggestion<\/a>
\n
Leonard Adolphs, Michelle Chen Huebscher<\/strong>, Christian Buck<\/strong>, Sertan Girgin<\/strong>, Olivier Bachem<\/strong>, Massimiliano Ciaramita<\/strong>, Thomas Hofmann<\/em>\n<\/p>\n

\nHyper-X: A Unified Hypernetwork for Multi-Task Multilingual Transfer<\/a>
\n
Ahmet \u00dcst\u00fcn, Arianna Bisazza, Gosse Bouma, Gertjan van Noord, Sebastian Ruder<\/strong><\/em>\n<\/p>\n

\nOffer a Different Perspective: Modeling the Belief Alignment of Arguments in Multi-party Debates<\/a>
\n
Suzanna Sia, Kokil Jaidka, Hansin Ahuja<\/strong>, Niyati Chhaya, Kevin Duh<\/em>\n<\/p>\n

\nMeta-Learning Fast Weight Language Model<\/a>
\n
Kevin Clark<\/b>, Kelvin Guu<\/b>, Ming-Wei Chang<\/b>, Panupong Pasupat<\/b>, Geoffrey Hinton<\/b>, Mohammad Norouzi<\/b><\/em>\n<\/p>\n

\nLarge Dual Encoders Are Generalizable Retrievers<\/a>
\n
Jianmo Ni<\/b>, Chen Qu<\/b>, Jing Lu<\/b>, Zhuyun Dai<\/b>, Gustavo Hern\u00e1ndez \u00c1brego<\/b>, Vincent Y. Zhao<\/b>, Yi Luan<\/b>, Keith B. Hall<\/b>, Ming-Wei Chang<\/b>, Yinfei Yang<\/b><\/em>\n<\/p>\n

\nCONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning<\/a>
\n
Zeqiu Wu*, Yi Luan<\/strong>, Hannah Rashkin<\/strong>, David Reitter<\/strong>, Hannaneh Hajishirzi, Mari Ostendorf, Gaurav Singh Tomar<\/strong><\/em>\n<\/p>\n

\nOvercoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation<\/a>
\n
Tu Vu*, Aditya Barua<\/strong>, Brian Lester<\/strong>, Daniel Cer<\/strong>, Mohit Iyyer, Noah Constant<\/strong><\/em>\n<\/p>\n

\nRankGen: Improving Text Generation with Large Ranking Models<\/a>
\n
Kalpesh Krishna, Yapei Chang, John Wieting<\/strong>, Mohit Iyyer<\/em>\n<\/p>\n

\nUnifiedSKG: Unifying and Multi-tasking Structured Knowledge Grounding with Text-to-Text Language Models<\/a>
\n
Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin<\/strong>, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer and Tao Yu<\/em>\n<\/p>\n

\nM2D2: A Massively Multi-domain Language Modeling Dataset<\/a>
\n
Machel Reid<\/b>, Victor Zhong<\/b>, Suchin Gururangan<\/b>, Luke Zettlemoyer<\/b><\/em>\n<\/p>\n

\nTomayto, Tomahto. Beyond Token-Level Answer Equivalence for Question Answering Evaluation<\/a>
\n
Jannis Bulian<\/b>, Christian Buck<\/b>, Wojciech Gajewski<\/b>, Benjamin Boerschinger<\/b>, Tal Schuster<\/b><\/em>\n<\/p>\n

\nCOCOA: An Encoder-Decoder Model for Controllable Code-Switched Generation<\/a>
\n
Sneha Mondal<\/b>, Ritika Goyal<\/b>, Shreya Pathak<\/b>, Preethi Jyothi<\/b>, Aravindan Raghuveer<\/b><\/em>\n<\/p>\n

\nCrossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset<\/a> (see blog post<\/a>)
\n
Ashish V. Thapliyal<\/b>, Jordi Pont-Tuset<\/b>, Xi Chen<\/b>, Radu Soricut<\/b><\/em>\n<\/p>\n

\n“Will You Find These Shortcuts?” A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification<\/a> (see blog post<\/a>)
\n
Jasmijn Bastings<\/b>, Sebastian Ebert<\/b>, Polina Zablotskaia<\/b>, Anders Sandholm<\/b>, Katja Filippova<\/b><\/em>\n<\/p>\n

\nIntriguing Properties of Compression on Multilingual Models<\/a>
\n
Kelechi Ogueji*, Orevaoghene Ahia, Gbemileke A. Onilude, Sebastian Gehrmann<\/strong>, Sara Hooker, Julia Kreutzer<\/strong><\/em>\n<\/p>\n

\nFETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue<\/a>
\n
Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi, Connor Pryor, Luke Yoffe, Deepak Ramachandran<\/strong>, Lise Getoor, Jay Pujara, William Yang Wang<\/em>\n<\/p>\n

\nSHARE: a System for Hierarchical Assistive Recipe Editing<\/a>
\n
Shuyang Li, Yufei Li, Jianmo Ni<\/strong>, Julian McAuley<\/em>\n<\/p>\n

\nContext Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics<\/a>
\n
Elisa Kreiss, Cynthia Bennett<\/strong>, Shayan Hooshmand, Eric Zelikman, Meredith Ringel Morris<\/strong>, Christopher Potts<\/em>\n<\/p>\n

\nJust Fine-Tune Twice: Selective Differential Privacy for Large Language Models<\/a>
\n
Weiyan Shi, Ryan Patrick Shea, Si Chen, Chiyuan Zhang<\/strong>, Ruoxi Jia, Zhou Yu<\/em>\n<\/p>\n

Findings of EMNLP<\/h2>\n

\nLeveraging Data Recasting to Enhance Tabular Reasoning<\/a>
\n
Aashna Jena, Manish Shrivastava, Vivek Gupta, Julian Martin Eisenschlos<\/strong><\/em>\n<\/p>\n

\nQUILL: Query Intent with Large Language Models Using Retrieval Augmentation and Multi-stage Distillation<\/a>
\n
Krishna Srinivasan<\/b>, Karthik Raman<\/b>, Anupam Samanta<\/b>, Lingrui Liao<\/b>, Luca Bertelli<\/b>, Michael Bendersky<\/b><\/em>\n<\/p>\n

\nAdapting Multilingual Models for Code-Mixed Translation<\/a>
\n
Aditya Vavre, Abhirut Gupta<\/strong>, Sunita Sarawagi\n<\/p>\n

\nTable-To-Text Generation and Pre-training with TABT5<\/a>
\n
Ewa Andrejczuk<\/b>, Julian Martin Eisenschlos<\/b>, Francesco Piccinno<\/b>, Syrine Krichene<\/b>, Yasemin Altun<\/b><\/em>\n<\/p>\n

\nStretching Sentence-Pair NLI Models to Reason Over Long Documents and Clusters<\/a>
\n
Tal Schuster<\/b>, Sihao Chen<\/b>, Senaka Buthpitiya<\/b>, Alex Fabrikant<\/b>, Donald Metzler<\/b><\/em>\n<\/p>\n

\nKnowledge-Grounded Dialog State Tracking<\/a>
\n
Dian Yu*, Mingqiu Wang<\/strong>, Yuan Cao<\/strong>, Izhak Shafran<\/strong>, Laurent El Shafey<\/strong>, Hagen Soltau<\/strong><\/em>\n<\/p>\n

\nSparse Mixers: Combining MoE and Mixing to Build a More Efficient BERT<\/a>
\n
James Lee-Thorp<\/b>, Joshua Ainslie<\/b><\/em>\n<\/p>\n

\nEdiT5: Semi-Autoregressive Text Editing with T5 Warm-Start<\/a>
\n
Jonathan Mallinson<\/b>, Jakub Adamek<\/b>, Eric Malmi<\/b>, Aliaksei Severyn<\/b><\/em>\n<\/p>\n

\nAutoregressive Structured Prediction with Language Models<\/a>
\n
Tianyu Liu, Yuchen Eleanor Jiang, Nicholas Monath<\/strong>, Ryan Cotterell and Mrinmaya Sachan<\/em>\n<\/p>\n

\nFaithful to the Document or to the World? Mitigating Hallucinations via Entity-Linked Knowledge in Abstractive Summarization<\/a>
\n
Yue Dong*, John Wieting<\/strong>, Pat Verga<\/strong><\/em>\n<\/p>\n

\nInvestigating Ensemble Methods for Model Robustness Improvement of Text Classifiers<\/a>
\n
Jieyu Zhao*, Xuezhi Wang<\/strong>, Yao Qin<\/strong>, Jilin Chen<\/strong>, Kai-Wei Chang<\/em>\n<\/p>\n

\nTopic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation<\/a>
\n
Dongha Lee, Jiaming Shen<\/strong>, Seonghyeon Lee, Susik Yoon, Hwanjo Yu, Jiawei Han<\/em>\n<\/p>\n

\nBenchmarking Language Models for Code Syntax Understanding<\/a>
\n
Da Shen, Xinyun Chen<\/strong>, Chenguang Wang, Koushik Sen, Dawn Song<\/em>\n<\/p>\n

\nLarge-Scale Differentially Private BERT<\/a>
\n
Rohan Anil<\/b>, Badih Ghazi<\/b>, Vineet Gupta<\/b>, Ravi Kumar<\/b>, Pasin Manurangsi<\/b><\/em>\n<\/p>\n

\nTowards Tracing Knowledge in Language Models Back to the Training Data<\/a>
\n
Ekin Akyurek, Tolga Bolukbasi<\/strong>, Frederick Liu<\/strong>, Binbin Xiong<\/strong>, Ian Tenney<\/strong>, Jacob Andreas, Kelvin Guu<\/strong><\/em>\n<\/p>\n

\nPredicting Long-Term Citations from Short-Term Linguistic Influence<\/a>
\n
Sandeep Soni, David Bamman, Jacob Eisenstein<\/strong><\/em>\n<\/p>\n

Workshops<\/h2>\n

\nWidening NLP<\/a>
\n
Organizers include: Shaily Bhatt<\/strong>, Sunipa Dev<\/strong>, Isidora Tourni<\/strong><\/em>\n<\/p>\n

\nThe First Workshop on Ever Evolving NLP (EvoNLP)<\/a>
\n
Organizers include: Bhuwan Dhingra<\/strong><\/em>
\n
Invited Speakers include: Eunsol Choi<\/strong>, Jacob Einstein<\/strong><\/em>\n<\/p>\n

\nMassively Multilingual NLU 2022<\/a>
\n
Invited Speakers include: Sebastian Ruder<\/strong><\/em>\n<\/p>\n

\nSecond Workshop on NLP for Positive Impact<\/a>
\n
Invited Speakers include: Milind Tambe<\/strong><\/em>\n<\/p>\n

\nBlackboxNLP – Workshop on Analyzing and Interpreting Neural Networks for NLP<\/a>
\n
Organizers include: Jasmijn Bastings<\/strong><\/em>\n<\/p>\n

\nMRL: The 2nd Workshop on Multi-lingual Representation Learning<\/a>
\n
Organizers include: Orhan Firat<\/strong>, Sebastian Ruder<\/strong><\/em>\n<\/p>\n

\nNovel Ideas in Learning-to-Learn Through Interaction (NILLI)<\/a>
\n
Program Committee includes: Yu-Siang Wang<\/strong><\/em>\n<\/p>\n

Tutorials<\/h2>\n

\nEmergent Language-Based Coordination In Deep Multi-Agent Systems
\n
Marco Baroni, Roberto Dessi, Angeliki Lazaridou<\/strong><\/em>\n<\/p>\n

\nTutorial on Causal Inference for Natural Language Processing
\n
Zhijing Jin, Amir Feder<\/strong>, Kun Zhang<\/em>\n<\/p>\n

\nModular and Parameter-Efficient Fine-Tuning for NLP Models
\n
Sebastian Ruder<\/b>, Jonas Pfeiffer<\/b>, Ivan Vulic<\/b><\/em>\n<\/p>\n

<\/p>\n

\n

\n * Work done while at Google<\/p>\n<\/div>\n

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