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ORCIDHinrich Schütze
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- affiliation: Ludwig Maximilian University of Munich, Center for Information and Language Processing, Germany
- affiliation (former): University of Stuttgart, Institute for Natural Language Processing, Germany
- affiliation (former): Stanford University, CA, USA
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2020 – today
- 2021
[c206]Timo Schick, Hinrich Schütze:
Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference. EACL 2021: 255-269- [c205]Lutfi Kerem Senel, Hinrich Schütze:
Does She Wink or Does She Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models. EACL 2021: 532-538 - [c204]Martin Schmitt, Hinrich Schütze:
Language Models for Lexical Inference in Context. EACL 2021: 1267-1280 - [c203]Nora Kassner, Philipp Dufter, Hinrich Schütze:
Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models. EACL 2021: 3250-3258 - [c202]Timo Schick, Hinrich Schütze:
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. NAACL-HLT 2021: 2339-2352 - [c201]Philipp Dufter, Nora Kassner, Hinrich Schütze:
Static Embeddings as Efficient Knowledge Bases? NAACL-HLT 2021: 2353-2363 - [c200]Pankaj Gupta, Yatin Chaudhary, Hinrich Schütze:
Multi-source Neural Topic Modeling in Multi-view Embedding Spaces. NAACL-HLT 2021: 4205-4217 - [i118]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
Superbizarre Is Not Superb: Improving BERT's Interpretations of Complex Words with Derivational Morphology. CoRR abs/2101.00403 (2021) - [i117]Nora Kassner, Philipp Dufter, Hinrich Schütze:
Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models. CoRR abs/2102.00894 (2021) - [i116]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg:
Measuring and Improving Consistency in Pretrained Language Models. CoRR abs/2102.01017 (2021) - [i115]Lutfi Kerem Senel, Hinrich Schütze:
Does He Wink or Does He Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models. CoRR abs/2102.03596 (2021) - [i114]Sahand Sharifzadeh, Sina Moayed Baharlou, Martin Schmitt, Hinrich Schütze, Volker Tresp:
Improving Visual Reasoning by Exploiting The Knowledge in Texts. CoRR abs/2102.04760 (2021) - [i113]Martin Schmitt, Hinrich Schütze:
Language Models for Lexical Inference in Context. CoRR abs/2102.05331 (2021) - [i112]Philipp Dufter, Martin Schmitt, Hinrich Schütze:
Position Information in Transformers: An Overview. CoRR abs/2102.11090 (2021) - [i111]Timo Schick, Sahana Udupa, Hinrich Schütze:
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP. CoRR abs/2103.00453 (2021) - [i110]Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schütze:
Few-Shot Learning of an Interleaved Text Summarization Model by Pretraining with Synthetic Data. CoRR abs/2103.05131 (2021) - [i109]Philipp Dufter, Nora Kassner, Hinrich Schütze:
Static Embeddings as Efficient Knowledge Bases? CoRR abs/2104.07094 (2021) - [i108]Timo Schick, Hinrich Schütze:
Generating Datasets with Pretrained Language Models. CoRR abs/2104.07540 (2021) - [i107]Nora Kassner, Oyvind Tafjord, Hinrich Schütze, Peter Clark:
Enriching a Model's Notion of Belief using a Persistent Memory. CoRR abs/2104.08401 (2021) - [i106]Pankaj Gupta, Yatin Chaudhary, Hinrich Schütze:
Multi-source Neural Topic Modeling in Multi-view Embedding Spaces. CoRR abs/2104.08551 (2021) - [i105]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
Modeling Ideological Agenda Setting and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity. CoRR abs/2104.08829 (2021) - 2020
- [j26]Dietrich Trautmann
, Michael Fromm, Volker Tresp, Thomas Seidl, Hinrich Schütze:
Relational and Fine-Grained Argument Mining. Datenbank-Spektrum 20(2): 99-105 (2020) - [c199]Alena Moiseeva, Hinrich Schütze:
TRENDNERT: A Benchmark for Trend and Downtrend Detection in a Scientific Domain. AAAI 2020: 8512-8519 - [c198]Timo Schick, Hinrich Schütze:
Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking. AAAI 2020: 8766-8774 - [c197]Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Schütze, Iryna Gurevych:
Fine-Grained Argument Unit Recognition and Classification. AAAI 2020: 9048-9056 - [c196]Valentin Hofmann, Hinrich Schütze, Janet B. Pierrehumbert:
A Graph Auto-encoder Model of Derivational Morphology. ACL 2020: 1127-1138 - [c195]Timo Schick, Hinrich Schütze:
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. ACL 2020: 3996-4007 - [c194]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity. ACL 2020: 7027-7034 - [c193]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
Predicting the Growth of Morphological Families from Social and Linguistic Factors. ACL 2020: 7273-7283 - [c192]Nora Kassner, Hinrich Schütze:
Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly. ACL 2020: 7811-7818 - [c191]Silvia Severini, Viktor Hangya, Alexander M. Fraser, Hinrich Schütze:
LMU Bilingual Dictionary Induction System with Word Surface Similarity Scores for BUCC 2020. BUCC@LREC 2020: 49-55 - [c190]Philipp Dufter, Martin Schmitt, Hinrich Schütze:
Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention. COLING 2020: 3630-3636 - [c189]Sheng Liang, Philipp Dufter, Hinrich Schütze:
Monolingual and Multilingual Reduction of Gender Bias in Contextualized Representations. COLING 2020: 5082-5093 - [c188]Timo Schick, Helmut Schmid, Hinrich Schütze:
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. COLING 2020: 5569-5578 - [c187]Silvia Severini, Viktor Hangya, Alexander M. Fraser, Hinrich Schütze:
Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction. COLING 2020: 6044-6055 - [c186]Nora Kassner, Benno Krojer, Hinrich Schütze:
Are Pretrained Language Models Symbolic Reasoners over Knowledge? CoNLL 2020: 552-564 - [c185]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT. EMNLP (Findings) 2020: 803-818 - [c184]Mengjie Zhao, Philipp Dufter, Yadollah Yaghoobzadeh, Hinrich Schütze:
Quantifying the Contextualization of Word Representations with Semantic Class Probing. EMNLP (Findings) 2020: 1219-1234 - [c183]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
Inexpensive Domain Adaptation of Pretrained Language Models: Case Studies on Biomedical NER and Covid-19 QA. EMNLP (Findings) 2020: 1482-1490 - [c182]Masoud Jalili Sabet, Philipp Dufter, François Yvon, Hinrich Schütze:
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings. EMNLP (Findings) 2020: 1627-1643 - [c181]Yatin Chaudhary, Pankaj Gupta, Khushbu Saxena, Vivek Kulkarni, Thomas A. Runkler, Hinrich Schütze:
TopicBERT for Energy Efficient Document Classification. EMNLP (Findings) 2020: 1682-1690 - [c180]Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schütze:
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models. EMNLP (1) 2020: 2226-2241 - [c179]Nora Kassner, Hinrich Schütze:
BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA. EMNLP (Findings) 2020: 3424-3430 - [c178]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
DagoBERT: Generating Derivational Morphology with a Pretrained Language Model. EMNLP (1) 2020: 3848-3861 - [c177]Philipp Dufter, Hinrich Schütze:
Identifying Elements Essential for BERT's Multilinguality. EMNLP (1) 2020: 4423-4437 - [c176]Martin Schmitt, Sahand Sharifzadeh, Volker Tresp, Hinrich Schütze:
An Unsupervised Joint System for Text Generation from Knowledge Graphs and Semantic Parsing. EMNLP (1) 2020: 7117-7130 - [c175]Yatin Chaudhary, Hinrich Schütze, Pankaj Gupta:
Explainable and Discourse Topic-aware Neural Language Understanding. ICML 2020: 1479-1488 - [c174]Pankaj Gupta, Yatin Chaudhary, Thomas A. Runkler, Hinrich Schütze:
Neural Topic Modeling with Continual Lifelong Learning. ICML 2020: 3907-3917 - [c173]Anne Beyer, Göran Kauermann, Hinrich Schütze:
Embedding Space Correlation as a Measure of Domain Similarity. LREC 2020: 2431-2439 - [c172]Suteera Seeha, Ivan Bilan, Liliana Mamani Sánchez, Johannes Huber, Michael Matuschek, Hinrich Schütze:
ThaiLMCut: Unsupervised Pretraining for Thai Word Segmentation. LREC 2020: 6947-6957 - [c171]Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze:
EmbLexChange at SemEval-2020 Task 1: Unsupervised Embedding-based Detection of Lexical Semantic Changes. SemEval@COLING 2020: 201-207 - [i104]Alena Moiseeva, Dietrich Trautmann, Hinrich Schütze:
Multipurpose Intelligent Process Automation via Conversational Assistant. CoRR abs/2001.02284 (2020) - [i103]Timo Schick, Hinrich Schütze:
Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference. CoRR abs/2001.07676 (2020) - [i102]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
Inexpensive Domain Adaptation of Pretrained Language Models: A Case Study on Biomedical Named Entity Recognition. CoRR abs/2004.03354 (2020) - [i101]Masoud Jalili Sabet, Philipp Dufter, Hinrich Schütze:
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings. CoRR abs/2004.08728 (2020) - [i100]Mengjie Zhao, Philipp Dufter, Yadollah Yaghoobzadeh, Hinrich Schütze:
Quantifying the Contextualization of Word Representations with Semantic Class Probing. CoRR abs/2004.12198 (2020) - [i99]Mengjie Zhao, Tao Lin, Martin Jaggi, Hinrich Schütze:
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models. CoRR abs/2004.12406 (2020) - [i98]Philipp Dufter, Hinrich Schütze:
Identifying Necessary Elements for BERT's Multilinguality. CoRR abs/2005.00396 (2020) - [i97]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
Generating Derivational Morphology with BERT. CoRR abs/2005.00672 (2020) - [i96]Nora Kassner, Hinrich Schütze:
BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA. CoRR abs/2005.00766 (2020) - [i95]Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze:
Unsupervised Embedding-based Detection of Lexical Semantic Changes. CoRR abs/2005.07979 (2020) - [i94]Martin Schmitt, Leonardo F. R. Ribeiro, Philipp Dufter, Iryna Gurevych, Hinrich Schütze:
Modeling Graph Structure via Relative Position for Better Text Generation from Knowledge Graphs. CoRR abs/2006.09242 (2020) - [i93]Nora Kassner, Benno Krojer, Hinrich Schütze:
Pre-trained Language Models as Symbolic Reasoners over Knowledge? CoRR abs/2006.10413 (2020) - [i92]Yatin Chaudhary, Hinrich Schütze, Pankaj Gupta:
Explainable and Discourse Topic-aware Neural Language Understanding. CoRR abs/2006.10632 (2020) - [i91]Pankaj Gupta, Yatin Chaudhary, Thomas A. Runkler, Hinrich Schütze:
Neural Topic Modeling with Continual Lifelong Learning. CoRR abs/2006.10909 (2020) - [i90]Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze:
Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes. CoRR abs/2006.14209 (2020) - [i89]Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, Iryna Gurevych:
Investigating Pretrained Language Models for Graph-to-Text Generation. CoRR abs/2007.08426 (2020) - [i88]Timo Schick, Hinrich Schütze:
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. CoRR abs/2009.07118 (2020) - [i87]Antonis Maronikolakis, Mark Stevenson, Hinrich Schütze:
Transformers Are Better Than Humans at Identifying Generated Text. CoRR abs/2009.13375 (2020) - [i86]Valentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze:
Dynamic Contextualized Word Embeddings. CoRR abs/2010.12684 (2020) - [i85]Timo Schick, Helmut Schmid, Hinrich Schütze:
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. CoRR abs/2010.13641 (2020) - [i84]Yatin Chaudhary, Pankaj Gupta, Khushbu Saxena, Vivek Kulkarni, Thomas A. Runkler, Hinrich Schütze:
TopicBERT for Energy Efficient Document Classification. CoRR abs/2010.16407 (2020) - [i83]Ehsaneddin Asgari, Masoud Jalili Sabet, Philipp Dufter, Christoph Ringlstetter, Hinrich Schütze:
Subword Sampling for Low Resource Word Alignment. CoRR abs/2012.11657 (2020) - [i82]Timo Schick, Hinrich Schütze:
Few-Shot Text Generation with Pattern-Exploiting Training. CoRR abs/2012.11926 (2020) - [i81]Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Roi Reichart, Anna Korhonen, Hinrich Schütze:
A Closer Look at Few-Shot Crosslingual Transfer: Variance, Benchmarks and Baselines. CoRR abs/2012.15682 (2020)
2010 – 2019
- 2019
- [j25]Heike Adel, Hinrich Schütze:
Type-aware Convolutional Neural Networks for Slot Filling. J. Artif. Intell. Res. 66: 297-339 (2019) - [j24]Benjamin Roth, Costanza Conforti, Nina Pörner, Sanjeev Kumar Karn, Hinrich Schütze:
Neural architectures for open-type relation argument extraction. Nat. Lang. Eng. 25(2): 219-238 (2019) - [j23]Marco Cornolti, Paolo Ferragina, Massimiliano Ciaramita, Stefan Rüd, Hinrich Schütze:
SMAPH: A Piggyback Approach for Entity-Linking in Web Queries. ACM Trans. Inf. Syst. 37(1): 13:1-13:42 (2019) - [c170]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
Document Informed Neural Autoregressive Topic Models with Distributional Prior. AAAI 2019: 6505-6512 - [c169]Pankaj Gupta, Subburam Rajaram, Hinrich Schütze, Thomas A. Runkler:
Neural Relation Extraction within and across Sentence Boundaries. AAAI 2019: 6513-6520 - [c168]Timo Schick, Hinrich Schütze:
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context. AAAI 2019: 6965-6973 - [c167]Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze:
Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes. ACL (1) 2019: 346-359 - [c166]Martin Schmitt, Hinrich Schütze:
SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference. ACL (1) 2019: 902-914 - [c165]Mengjie Zhao, Hinrich Schütze:
A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction. ACL (1) 2019: 3506-3517 - [c164]Yadollah Yaghoobzadeh, Katharina Kann, Timothy J. Hazen, Eneko Agirre, Hinrich Schütze:
Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings. ACL (1) 2019: 5740-5753 - [c163]Pankaj Gupta, Usama Yaseen, Hinrich Schütze:
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019. BioNLP-OST@EMNLP-IJNCLP 2019: 132-142 - [c162]Pankaj Gupta, Yatin Chaudhary, Hinrich Schütze:
BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions. BioNLP-OST@EMNLP-IJNCLP 2019: 227-236 - [c161]Philipp Dufter, Hinrich Schütze:
Analytical Methods for Interpretable Ultradense Word Embeddings. EMNLP/IJCNLP (1) 2019: 1185-1191 - [c160]Nina Pörner, Hinrich Schütze:
Multi-View Domain Adapted Sentence Embeddings for Low-Resource Unsupervised Duplicate Question Detection. EMNLP/IJCNLP (1) 2019: 1630-1641 - [c159]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior. ICLR (Poster) 2019 - [c158]Shahbaz Syed, Michael Völske, Nedim Lipka, Benno Stein, Hinrich Schütze, Martin Potthast:
Towards Summarization for Social Media - Results of the TL;DR Challenge. INLG 2019: 523-528 - [c157]Timo Schick, Hinrich Schütze:
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts. NAACL-HLT (1) 2019: 489-494 - [c156]Apostolos Kemos, Heike Adel, Hinrich Schütze:
Neural Semi-Markov Conditional Random Fields for Robust Character-Based Part-of-Speech Tagging. NAACL-HLT (1) 2019: 2736-2743 - [c155]Sanjeev Kumar Karn, Mark Buckley, Ulli Waltinger, Hinrich Schütze:
News Article Teaser Tweets and How to Generate Them. NAACL-HLT (1) 2019: 3967-3977 - [i80]Timo Schick, Hinrich Schütze:
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts. CoRR abs/1904.01617 (2019) - [i79]Timo Schick, Hinrich Schütze:
Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking. CoRR abs/1904.06707 (2019) - [i78]Philipp Dufter, Hinrich Schütze:
Analytical Methods for Interpretable Ultradense Word Embeddings. CoRR abs/1904.08654 (2019) - [i77]Martin Schmitt, Hinrich Schütze:
Unsupervised Text Generation from Structured Data. CoRR abs/1904.09447 (2019) - [i76]Dietrich Trautmann, Johannes Daxenberger, Christian Stab, Hinrich Schütze, Iryna Gurevych:
Robust Argument Unit Recognition and Classification. CoRR abs/1904.09688 (2019) - [i75]Martin Schmitt, Hinrich Schütze:
SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference. CoRR abs/1906.01393 (2019) - [i74]Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schütze:
Generating Multi-Sentence Abstractive Summaries of Interleaved Texts. CoRR abs/1906.01973 (2019) - [i73]Yadollah Yaghoobzadeh, Katharina Kann, Timothy J. Hazen, Eneko Agirre, Hinrich Schütze:
Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings. CoRR abs/1906.03608 (2019) - [i72]Ryan Cotterell, Hinrich Schütze:
Morphological Word Embeddings. CoRR abs/1907.02423 (2019) - [i71]Pankaj Gupta, Khushbu Saxena, Usama Yaseen, Thomas A. Runkler, Hinrich Schütze:
Neural Architectures for Fine-Grained Propaganda Detection in News. CoRR abs/1909.06162 (2019) - [i70]Pankaj Gupta, Yatin Chaudhary, Hinrich Schütze:
Multi-view and Multi-source Transfers in Neural Topic Modeling with Pretrained Topic and Word Embeddings. CoRR abs/1909.06563 (2019) - [i69]Yatin Chaudhary, Pankaj Gupta, Hinrich Schütze:
BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions. CoRR abs/1910.00314 (2019) - [i68]Heike Adel, Hinrich Schütze:
Type-aware Convolutional Neural Networks for Slot Filling. CoRR abs/1910.00546 (2019) - [i67]Usama Yaseen, Pankaj Gupta, Hinrich Schütze:
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019. CoRR abs/1910.03385 (2019) - [i66]Timo Schick, Hinrich Schütze:
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. CoRR abs/1910.07181 (2019) - [i65]Nora Kassner, Hinrich Schütze:
Negated LAMA: Birds cannot fly. CoRR abs/1911.03343 (2019) - [i64]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
BERT is Not a Knowledge Base (Yet): Factual Knowledge vs. Name-Based Reasoning in Unsupervised QA. CoRR abs/1911.03681 (2019) - [i63]Nina Pörner, Ulli Waltinger, Hinrich Schütze:
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity. CoRR abs/1911.03700 (2019) - [i62]Ryan Cotterell, Arun Kumar, Hinrich Schütze:
Morphological Segmentation Inside-Out. CoRR abs/1911.04916 (2019) - [i61]James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze:
Extending Machine Language Models toward Human-Level Language Understanding. CoRR abs/1912.05877 (2019) - 2018
- [j22]Yadollah Yaghoobzadeh, Heike Adel, Hinrich Schütze:
Corpus-Level Fine-Grained Entity Typing. J. Artif. Intell. Res. 61: 835-862 (2018) - [j21]Ryan Cotterell, Hinrich Schütze:
Joint Semantic Synthesis and Morphological Analysis of the Derived Word. Trans. Assoc. Comput. Linguistics 6: 33-48 (2018) - [j20]Wenpeng Yin, Hinrich Schütze:
Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms. Trans. Assoc. Comput. Linguistics 6: 687-702 (2018) - [c154]Nina Pörner, Hinrich Schütze, Benjamin Roth:
Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement. ACL (1) 2018: 340-350 - [c153]Wenpeng Yin, Dan Roth, Hinrich Schütze:
End-Task Oriented Textual Entailment via Deep Explorations of Inter-Sentence Interactions. ACL (2) 2018: 540-545 - [c152]Viktor Hangya, Fabienne Braune, Alexander M. Fraser, Hinrich Schütze:
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly Applicable. ACL (1) 2018: 810-820 - [c151]Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander M. Fraser, Hinrich Schütze:
Embedding Learning Through Multilingual Concept Induction. ACL (1) 2018: 1520-1530 - [c150]Wenpeng Yin, Yadollah Yaghoobzadeh, Hinrich Schütze:
Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs. COLING 2018: 2369-2378 - [c149]Pankaj Gupta, Hinrich Schütze:
LISA: Explaining Recurrent Neural Network Judgments via Layer-wIse Semantic Accumulation and Example to Pattern Transformation. BlackboxNLP@EMNLP 2018: 154-164 - [c148]Nina Pörner, Benjamin Roth, Hinrich Schütze:
Interpretable Textual Neuron Representations for NLP. BlackboxNLP@EMNLP 2018: 325-327 - [c147]Yadollah Yaghoobzadeh, Hinrich Schütze:
Multi-View Learning: Multilingual and Multi-Representation Entity Typing. EMNLP 2018: 3060-3066 - [c146]Katharina Kann, Hinrich Schütze:
Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting. EMNLP 2018: 3254-3264 - [c145]Shahbaz Syed, Michael Völske, Martin Potthast, Nedim Lipka, Benno Stein, Hinrich Schütze:
Task Proposal: The TL;DR Challenge. INLG 2018: 318-321 - [c144]Pankaj Gupta, Benjamin Roth, Hinrich Schütze:
Joint Bootstrapping Machines for High Confidence Relation Extraction. NAACL-HLT 2018: 26-36 - [c143]Katharina Kann, Manuel Mager, Iván Vladimir Meza Ruíz, Hinrich Schütze:
Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages. NAACL-HLT 2018: 47-57 - [c142]