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2020 – today
- 2025
[i46]Ting-Rui Chiang, Dani Yogatama:
The Rotary Position Embedding May Cause Dimension Inefficiency in Attention Heads for Long-Distance Retrieval. CoRR abs/2502.11276 (2025)- 2024
- [c37]Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg:
Interpretable Diffusion via Information Decomposition. ICLR 2024 - [c36]Ting-Rui Chiang, Xinyan Yu, Joshua Robinson, Ollie Liu, Isabelle Lee, Dani Yogatama:
On Retrieval Augmentation and the Limitations of Language Model Training. NAACL (Short Papers) 2024: 229-238 - [i45]Ollie Liu, Deqing Fu, Dani Yogatama, Willie Neiswanger:
DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models. CoRR abs/2402.02392 (2024) - [i44]Ting-Rui Chiang, Dani Yogatama:
Understanding In-Context Learning with a Pelican Soup Framework. CoRR abs/2402.10424 (2024) - [i43]Deqing Fu, Ghazal Khalighinejad, Ollie Liu, Bhuwan Dhingra, Dani Yogatama, Robin Jia, Willie Neiswanger:
IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations. CoRR abs/2404.01266 (2024) - [i42]Aitor Ormazabal, Che Zheng, Cyprien de Masson d'Autume, Dani Yogatama, Deyu Fu, Donovan Ong, Eric Chen, Eugenie Lamprecht, Hai Pham, Isaac Ong, Kaloyan Aleksiev, Lei Li, Matthew Henderson, Max Bain, Mikel Artetxe, Nishant Relan, Piotr Padlewski, Qi Liu, Ren Chen, Samuel Phua, Yazheng Yang, Yi Tay, Yuqi Wang
, Zhongkai Zhu, Zhihui Xie:
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models. CoRR abs/2404.12387 (2024) - [i41]Piotr Padlewski, Max Bain, Matthew Henderson, Zhongkai Zhu, Nishant Relan, Hai Pham, Donovan Ong, Kaloyan Aleksiev, Aitor Ormazabal, Samuel Phua, Ethan Yeo, Eugenie Lamprecht, Qi Liu, Yuqi Wang, Eric Chen, Deyu Fu, Lei Li, Che Zheng, Cyprien de Masson d'Autume, Dani Yogatama, Mikel Artetxe, Yi Tay:
Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models. CoRR abs/2405.02287 (2024) - [i40]Ting-Rui Chiang, Joshua Robinson, Xinyan Velocity Yu, Dani Yogatama:
LocateBench: Evaluating the Locating Ability of Vision Language Models. CoRR abs/2410.19808 (2024) - [i39]Isabelle Lee, Joshua Lum, Ziyi Liu, Dani Yogatama:
Causal Interventions on Causal Paths: Mapping GPT-2's Reasoning From Syntax to Semantics. CoRR abs/2410.21353 (2024) - [i38]Zhaofeng Wu, Xinyan Velocity Yu, Dani Yogatama, Jiasen Lu, Yoon Kim:
The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities. CoRR abs/2411.04986 (2024) - 2023
- [j9]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. Trans. Assoc. Comput. Linguistics 11: 600-616 (2023) - [j8]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Jeffrey Tsaw, Yudong Liu, Shentong Mo, Dani Yogatama, Louis-Philippe Morency, Russ Salakhutdinov:
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c35]Ting-Rui Chiang, Dani Yogatama:
The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining. EMNLP 2023: 10305-10321 - [c34]Yi Tay, Mostafa Dehghani, Samira Abnar, Hyung Won Chung, William Fedus, Jinfeng Rao, Sharan Narang, Vinh Q. Tran, Dani Yogatama, Donald Metzler:
Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? EMNLP (Findings) 2023: 12342-12364 - [i37]Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg:
Interpretable Diffusion via Information Decomposition. CoRR abs/2310.07972 (2023) - [i36]Ting-Rui Chiang, Dani Yogatama:
The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining. CoRR abs/2310.16261 (2023) - [i35]Ting-Rui Chiang, Xinyan Velocity Yu, Joshua Robinson, Ollie Liu, Isabelle Lee, Dani Yogatama:
On Retrieval Augmentation and the Limitations of Language Model Training. CoRR abs/2311.09615 (2023) - 2022
- [j7]Qi Liu, Dani Yogatama, Phil Blunsom:
Relational Memory-Augmented Language Models. Trans. Assoc. Comput. Linguistics 10: 555-572 (2022) - [j6]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - [c33]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. ACL (1) 2022: 7469-7483 - [c32]Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler:
Scale Efficiently: Insights from Pretraining and Finetuning Transformers. ICLR 2022 - [c31]Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, Nigel Collier:
A Contrastive Framework for Neural Text Generation. NeurIPS 2022 - [i34]Qi Liu, Dani Yogatama, Phil Blunsom:
Relational Memory Augmented Language Models. CoRR abs/2201.09680 (2022) - [i33]Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, Nigel Collier:
A Contrastive Framework for Neural Text Generation. CoRR abs/2202.06417 (2022) - [i32]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Shentong Mo, Dani Yogatama, Louis-Philippe Morency, Ruslan Salakhutdinov:
HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning. CoRR abs/2203.01311 (2022) - [i31]Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lingpeng Kong, Nigel Collier:
Language Models Can See: Plugging Visual Controls in Text Generation. CoRR abs/2205.02655 (2022) - [i30]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i29]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. CoRR abs/2206.10658 (2022) - [i28]Yi Tay, Mostafa Dehghani, Samira Abnar, Hyung Won Chung, William Fedus, Jinfeng Rao, Sharan Narang, Vinh Q. Tran, Dani Yogatama, Donald Metzler:
Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? CoRR abs/2207.10551 (2022) - 2021
- [j5]Dani Yogatama, Cyprien de Masson d'Autume, Lingpeng Kong:
Adaptive Semiparametric Language Models. Trans. Assoc. Comput. Linguistics 9: 362-373 (2021) - [c30]Jungo Kasai, Hao Peng, Yizhe Zhang, Dani Yogatama, Gabriel Ilharco, Nikolaos Pappas, Yi Mao, Weizhu Chen, Noah A. Smith:
Finetuning Pretrained Transformers into RNNs. EMNLP (1) 2021: 10630-10643 - [c29]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. ICLR 2021 - [c28]Stefan Daniel Dumitrescu, Petru Rebeja, Beáta Lorincz, Mihaela Gaman, Andrei-Marius Avram, Mihai Ilie, Andrei Pruteanu, Adriana Stan, Lorena Rosia, Cristina Iacobescu, Luciana Morogan, George Dima, Gabriel Marchidan, Traian Rebedea, Madalina Chitez, Dani Yogatama, Sebastian Ruder, Radu Tudor Ionescu, Razvan Pascanu, Viorica Patraucean:
LiRo: Benchmark and leaderboard for Romanian language tasks. NeurIPS Datasets and Benchmarks 2021 - [c27]Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama:
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. NeurIPS 2021: 25968-25981 - [c26]Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska, Tayfun Terzi, Mai Gimenez, Cyprien de Masson d'Autume, Tomás Kociský, Sebastian Ruder, Dani Yogatama, Kris Cao, Susannah Young, Phil Blunsom:
Mind the Gap: Assessing Temporal Generalization in Neural Language Models. NeurIPS 2021: 29348-29363 - [i27]Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska, Tayfun Terzi, Mai Gimenez, Cyprien de Masson d'Autume, Sebastian Ruder, Dani Yogatama, Kris Cao, Tomás Kociský, Susannah Young, Phil Blunsom:
Pitfalls of Static Language Modelling. CoRR abs/2102.01951 (2021) - [i26]Dani Yogatama, Cyprien de Masson d'Autume, Lingpeng Kong:
Adaptive Semiparametric Language Models. CoRR abs/2102.02557 (2021) - [i25]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. CoRR abs/2103.02143 (2021) - [i24]Jungo Kasai, Hao Peng, Yizhe Zhang, Dani Yogatama, Gabriel Ilharco, Nikolaos Pappas, Yi Mao, Weizhu Chen, Noah A. Smith:
Finetuning Pretrained Transformers into RNNs. CoRR abs/2103.13076 (2021) - [i23]Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama:
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. CoRR abs/2106.05346 (2021) - [i22]Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler:
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers. CoRR abs/2109.10686 (2021) - [i21]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. CoRR abs/2110.02488 (2021) - [i20]Paul Michel, Sebastian Ruder, Dani Yogatama:
Balancing Average and Worst-case Accuracy in Multitask Learning. CoRR abs/2110.05838 (2021) - 2020
- [j4]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining for Bidirectional Encoders. Trans. Assoc. Comput. Linguistics 8: 776-794 (2020) - [c25]Mikel Artetxe, Sebastian Ruder, Dani Yogatama:
On the Cross-lingual Transferability of Monolingual Representations. ACL 2020: 4623-4637 - [c24]Mikel Artetxe, Sebastian Ruder, Dani Yogatama, Gorka Labaka, Eneko Agirre:
A Call for More Rigor in Unsupervised Cross-lingual Learning. ACL 2020: 7375-7388 - [c23]Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli:
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. EMNLP (Findings) 2020: 65-83 - [c22]Lingpeng Kong, Cyprien de Masson d'Autume, Lei Yu, Wang Ling, Zihang Dai, Dani Yogatama:
A Mutual Information Maximization Perspective of Language Representation Learning. ICLR 2020 - [i19]Kris Cao, Dani Yogatama:
Modelling Latent Skills for Multitask Language Generation. CoRR abs/2002.09543 (2020) - [i18]Mikel Artetxe, Sebastian Ruder, Dani Yogatama, Gorka Labaka, Eneko Agirre:
A Call for More Rigor in Unsupervised Cross-lingual Learning. CoRR abs/2004.14958 (2020) - [i17]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining For Bidirectional Encoders. CoRR abs/2005.13482 (2020)
2010 – 2019
- 2019
- [j3]Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver:
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - [j2]Jean Maillard, Stephen Clark, Dani Yogatama:
Jointly learning sentence embeddings and syntax with unsupervised Tree-LSTMs. Nat. Lang. Eng. 25(4): 433-449 (2019) - [c21]Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli:
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. EMNLP/IJCNLP (1) 2019: 4081-4091 - [c20]Lingpeng Kong, Gábor Melis, Wang Ling, Lei Yu, Dani Yogatama:
Variational Smoothing in Recurrent Neural Network Language Models. ICLR (Poster) 2019 - [c19]Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama:
Episodic Memory in Lifelong Language Learning. NeurIPS 2019: 13122-13131 - [i16]Lingpeng Kong, Gábor Melis, Wang Ling, Lei Yu, Dani Yogatama:
Variational Smoothing in Recurrent Neural Network Language Models. CoRR abs/1901.09296 (2019) - [i15]Dani Yogatama, Cyprien de Masson d'Autume, Jerome T. Connor, Tomás Kociský, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, Phil Blunsom:
Learning and Evaluating General Linguistic Intelligence. CoRR abs/1901.11373 (2019) - [i14]Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama:
Episodic Memory in Lifelong Language Learning. CoRR abs/1906.01076 (2019) - [i13]Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli:
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. CoRR abs/1909.01492 (2019) - [i12]Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling, Lei Yu, Zihang Dai, Dani Yogatama:
A Mutual Information Maximization Perspective of Language Representation Learning. CoRR abs/1910.08350 (2019) - [i11]Mikel Artetxe, Sebastian Ruder, Dani Yogatama:
On the Cross-lingual Transferability of Monolingual Representations. CoRR abs/1910.11856 (2019) - [i10]Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, Pushmeet Kohli:
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. CoRR abs/1911.03064 (2019) - 2018
- [c18]Adhiguna Kuncoro, Chris Dyer, John Hale, Dani Yogatama, Stephen Clark, Phil Blunsom:
LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better. ACL (1) 2018: 1426-1436 - [c17]Dani Yogatama, Yishu Miao, Gábor Melis, Wang Ling, Adhiguna Kuncoro, Chris Dyer, Phil Blunsom:
Memory Architectures in Recurrent Neural Network Language Models. ICLR (Poster) 2018 - 2017
- [c16]Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom:
Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. ACL (1) 2017: 158-167 - [c15]Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling:
Learning to Compose Words into Sentences with Reinforcement Learning. ICLR (Poster) 2017 - [i9]Dani Yogatama, Chris Dyer, Wang Ling, Phil Blunsom:
Generative and Discriminative Text Classification with Recurrent Neural Networks. CoRR abs/1703.01898 (2017) - [i8]Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom:
Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. CoRR abs/1705.04146 (2017) - [i7]Jean Maillard, Stephen Clark, Dani Yogatama:
Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs. CoRR abs/1705.09189 (2017) - 2016
- [c14]Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Awni Y. Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu:
Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. ICML 2016: 173-182 - [i6]Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling:
Learning to Compose Words into Sentences with Reinforcement Learning. CoRR abs/1611.09100 (2016) - 2015
- [c13]Dani Yogatama, Daniel Gillick, Nevena Lazic:
Embedding Methods for Fine Grained Entity Type Classification. ACL (2) 2015: 291-296 - [c12]Manaal Faruqui, Yulia Tsvetkov, Dani Yogatama, Chris Dyer, Noah A. Smith:
Sparse Overcomplete Word Vector Representations. ACL (1) 2015: 1491-1500 - [c11]Dani Yogatama, Fei Liu, Noah A. Smith:
Extractive Summarization by Maximizing Semantic Volume. EMNLP 2015: 1961-1966 - [c10]Dani Yogatama, Lingpeng Kong, Noah A. Smith:
Bayesian Optimization of Text Representations. EMNLP 2015: 2100-2105 - [c9]Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah A. Smith:
Learning Word Representations with Hierarchical Sparse Coding. ICML 2015: 87-96 - [i5]Dani Yogatama, Noah A. Smith:
Bayesian Optimization of Text Representations. CoRR abs/1503.00693 (2015) - [i4]Manaal Faruqui, Yulia Tsvetkov, Dani Yogatama, Chris Dyer, Noah A. Smith:
Sparse Overcomplete Word Vector Representations. CoRR abs/1506.02004 (2015) - [i3]Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Y. Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu:
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. CoRR abs/1512.02595 (2015) - 2014
- [j1]Dani Yogatama, Chong Wang, Bryan R. Routledge, Noah A. Smith, Eric P. Xing:
Dynamic Language Models for Streaming Text. Trans. Assoc. Comput. Linguistics 2: 181-192 (2014) - [c8]Dani Yogatama, Noah A. Smith:
Linguistic Structured Sparsity in Text Categorization. ACL (1) 2014: 786-796 - [c7]Dani Yogatama, Gideon Mann:
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning. AISTATS 2014: 1077-1085 - [c6]Dani Yogatama, Noah A. Smith:
Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers. ICML 2014: 656-664 - [i2]Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah A. Smith:
Learning Word Representations with Hierarchical Sparse Coding. CoRR abs/1406.2035 (2014) - 2013
- [c5]Tae Yano, Dani Yogatama, Noah A. Smith:
A Penny for Your Tweets: Campaign Contributions and Capitol Hill Microblogs. ICWSM 2013 - [i1]Dani Yogatama, Bryan R. Routledge, Noah A. Smith:
A Sparse and Adaptive Prior for Time-Dependent Model Parameters. CoRR abs/1310.2627 (2013) - 2012
- [c4]Dani Yogatama, Yanchuan Sim, Noah A. Smith:
A Probabilistic Model for Canonicalizing Named Entity Mentions. ACL (1) 2012: 685-693 - 2011
- [c3]Kevin Gimpel, Nathan Schneider, Brendan O'Connor, Dipanjan Das, Daniel Mills, Jacob Eisenstein, Michael Heilman, Dani Yogatama, Jeffrey Flanigan, Noah A. Smith:
Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments. ACL (2) 2011: 42-47 - [c2]Dani Yogatama, Michael Heilman, Brendan O'Connor, Chris Dyer, Bryan R. Routledge, Noah A. Smith:
Predicting a Scientific Community's Response to an Article. EMNLP 2011: 594-604
2000 – 2009
- 2009
- [c1]Dani Yogatama, Kumiko Tanaka-Ishii:
Multilingual Spectral Clustering Using Document Similarity Propagation. EMNLP 2009: 871-879
Coauthor Index
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