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ORCIDTrevor Cohn
Trevor Anthony Cohn
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- affiliation: University of Melbourne, School of Computing and Information Systems, Australia
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2020 – today
- 2023
[c181]Terry Yue Zhuo, Qiongkai Xu, Xuanli He, Trevor Cohn:
Rethinking Round-Trip Translation for Machine Translation Evaluation. ACL (Findings) 2023: 319-337- [c180]Sayantan Dasgupta, Trevor Cohn, Timothy Baldwin:
Cost-effective Distillation of Large Language Models. ACL (Findings) 2023: 7346-7354 - [c179]Zheng Wei Lim, Trevor Cohn, Charles Kemp, Ekaterina Vylomova:
Predicting Human Translation Difficulty Using Automatic Word Alignment. ACL (Findings) 2023: 11590-11601 - [c178]Qin Zhang, Shangsi Chen, Dongkuan Xu, Qingqing Cao, Xiaojun Chen, Trevor Cohn, Meng Fang:
A Survey for Efficient Open Domain Question Answering. ACL (1) 2023: 14447-14465 - [c177]Xudong Han, Timothy Baldwin, Trevor Cohn:
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP. EACL 2023: 297-312 - [c176]Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Lea Frermann:
Probing Power by Prompting: Harnessing Pre-trained Language Models for Power Connotation Framing. EACL 2023: 873-885 - [c175]Viktoria Schram, Daniel Beck, Trevor Cohn:
Performance Prediction via Bayesian Matrix Factorisation for Multilingual Natural Language Processing Tasks. EACL 2023: 1782-1793 - [c174]Fan Jiang, Tom Drummond, Trevor Cohn:
Don't Mess with Mister-in-Between: Improved Negative Search for Knowledge Graph Completion. EACL 2023: 1810-1824 - [c173]Xudong Han, Timothy Baldwin, Trevor Cohn:
Everybody Needs Good Neighbours: An Unsupervised Locality-based Method for Bias Mitigation. ICLR 2023 - [c172]Thinh Hung Truong, Timothy Baldwin, Karin Verspoor, Trevor Cohn:
Language models are not naysayers: an analysis of language models on negation benchmarks. *SEM@ACL 2023: 101-114 - [c171]Chunhua Liu, Trevor Cohn, Lea Frermann:
Seeking Clozure: Robust Hypernym extraction from BERT with Anchored Prompts. *SEM@ACL 2023: 193-206 - [i84]Zhuohan Xie, Trevor Cohn, Jey Han Lau:
Can Very Large Pretrained Language Models Learn Storytelling With A Few Examples? CoRR abs/2301.09790 (2023) - [i83]Xudong Han, Timothy Baldwin, Trevor Cohn:
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP. CoRR abs/2302.05711 (2023) - [i82]Zhuohan Xie, Miao Li, Trevor Cohn, Jey Han Lau:
DeltaScore: Evaluating Story Generation with Differentiating Perturbations. CoRR abs/2303.08991 (2023) - [i81]Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. CoRR abs/2305.11596 (2023) - [i80]Xuanli He, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks. CoRR abs/2305.16503 (2023) - [i79]Sukai Huang, Nir Lipovetzky, Trevor Cohn:
A Reminder of its Brittleness: Language Reward Shaping May Hinder Learning for Instruction Following Agents. CoRR abs/2305.16621 (2023) - [i78]Thinh Hung Truong, Timothy Baldwin, Karin Verspoor, Trevor Cohn:
Language models are not naysayers: An analysis of language models on negation benchmarks. CoRR abs/2306.08189 (2023) - 2022
- [c170]Fan Jiang, Trevor Cohn:
Incorporating Constituent Syntax for Coreference Resolution. AAAI 2022: 10831-10839 - [c169]Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
Measuring and Mitigating Name Biases in Neural Machine Translation. ACL (1) 2022: 2576-2590 - [c168]Yulia Otmakhova, Thinh Hung Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor, Jey Han Lau:
LED down the rabbit hole: exploring the potential of global attention for biomedical multi-document summarisation. SDP@COLING 2022: 181-187 - [c167]Yuan Li, Biaoyan Fang, Jiayuan He, Hiyori Yoshikawa, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Zenan Zhai, Zubair Afzal, Trevor Cohn, Timothy Baldwin, Karin Verspoor
:
The ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents. ECIR (2) 2022: 400-407 - [c166]Xudong Han, Aili Shen, Yitong Li, Lea Frermann, Timothy Baldwin, Trevor Cohn:
FairLib: A Unified Framework for Assessing and Improving Fairness. EMNLP (Demos) 2022: 60-71 - [c165]Jun Wang, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn:
Foiling Training-Time Attacks on Neural Machine Translation Systems. EMNLP (Findings) 2022: 5906-5913 - [c164]Xudong Han, Timothy Baldwin, Trevor Cohn:
Balancing out Bias: Achieving Fairness Through Balanced Training. EMNLP 2022: 11335-11350 - [c163]Xudong Han, Aili Shen, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Systematic Evaluation of Predictive Fairness. AACL/IJCNLP (1) 2022: 68-81 - [c162]Aili Shen, Xudong Han, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Does Representational Fairness Imply Empirical Fairness? AACL/IJCNLP (Findings) 2022: 81-95 - [c161]Chunhua Liu, Trevor Cohn, Simon De Deyne, Lea Frermann:
WAX: A New Dataset for Word Association eXplanations. AACL/IJCNLP (1) 2022: 106-120 - [c160]Thinh Hung Truong, Yulia Otmakhova, Timothy Baldwin, Trevor Cohn, Jey Han Lau, Karin Verspoor:
Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation. AACL/IJCNLP (1) 2022: 883-894 - [c159]Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn:
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source Data. NAACL-HLT 2022: 2041-2054 - [c158]Aili Shen, Xudong Han, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Optimising Equal Opportunity Fairness in Model Training. NAACL-HLT 2022: 4073-4084 - [c157]Thinh Hung Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor:
Improving negation detection with negation-focused pre-training. NAACL-HLT 2022: 4188-4193 - [i77]Thinh Hung Truong, Yulia Otmakhova, Rahmad Mahendra, Timothy Baldwin, Jey Han Lau, Trevor Cohn, Lawrence Cavedon, Damiano Spina, Karin Verspoor:
ITTC @ TREC 2021 Clinical Trials Track. CoRR abs/2202.07858 (2022) - [i76]Fan Jiang, Trevor Cohn:
Incorporating Constituent Syntax for Coreference Resolution. CoRR abs/2202.10710 (2022) - [i75]Xudong Han, Timothy Baldwin, Trevor Cohn:
Towards Equal Opportunity Fairness through Adversarial Learning. CoRR abs/2203.06317 (2022) - [i74]Xudong Han, Aili Shen, Yitong Li, Lea Frermann, Timothy Baldwin, Trevor Cohn:
fairlib: A Unified Framework for Assessing and Improving Classification Fairness. CoRR abs/2205.01876 (2022) - [i73]Aili Shen, Xudong Han, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Optimising Equal Opportunity Fairness in Model Training. CoRR abs/2205.02393 (2022) - [i72]Thinh Hung Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor:
Improving negation detection with negation-focused pre-training. CoRR abs/2205.04012 (2022) - [i71]Terry Yue Zhuo, Qiongkai Xu, Xuanli He, Trevor Cohn:
Rethinking Round-trip Translation for Automatic Machine Translation Evaluation. CoRR abs/2209.07351 (2022) - [i70]Yulia Otmakhova, Thinh Hung Truong, Timothy Baldwin, Trevor Cohn, Karin Verspoor, Jey Han Lau:
LED down the rabbit hole: exploring the potential of global attention for biomedical multi-document summarisation. CoRR abs/2209.08698 (2022) - [i69]Thinh Hung Truong, Yulia Otmakhova, Timothy Baldwin, Trevor Cohn, Jey Han Lau, Karin Verspoor:
Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation. CoRR abs/2210.03256 (2022) - [i68]Xudong Han, Aili Shen, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Systematic Evaluation of Predictive Fairness. CoRR abs/2210.08758 (2022) - [i67]You Guo, Jun Wang, Trevor Cohn:
Detecting Backdoors in Deep Text Classifiers. CoRR abs/2210.11264 (2022) - [i66]Qin Zhang, Shangsi Chen, Dongkuan Xu, Qingqing Cao, Xiaojun Chen, Trevor Cohn, Meng Fang:
A Survey for Efficient Open Domain Question Answering. CoRR abs/2211.07886 (2022) - 2021
- [j14]Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor:
ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents. Frontiers Res. Metrics Anal. 6: 654438 (2021) - [j13]Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Dat Quoc Nguyen, Trevor Cohn, Karin Verspoor:
ChemTables: a dataset for semantic classification on tables in chemical patents. J. Cheminformatics 13(1): 97 (2021) - [c156]Xudong Han, Timothy Baldwin, Trevor Cohn:
Decoupling Adversarial Training for Fair NLP. ACL/IJCNLP (Findings) 2021: 471-477 - [c155]Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn:
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. ACL/IJCNLP (Findings) 2021: 1463-1473 - [c154]Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn:
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. ACL/IJCNLP (Findings) 2021: 4711-4717 - [c153]Chunhua Liu, Trevor Cohn, Lea Frermann:
Commonsense Knowledge in Word Associations and ConceptNet. CoNLL 2021: 481-495 - [c152]Philip Arthur, Trevor Cohn, Gholamreza Haffari:
Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning. EACL 2021: 2709-2719 - [c151]Xudong Han, Timothy Baldwin, Trevor Cohn:
Diverse Adversaries for Mitigating Bias in Training. EACL 2021: 2760-2765 - [c150]Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn:
PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation. EACL 2021: 2907-2918 - [c149]Jiayuan He, Biaoyan Fang, Hiyori Yoshikawa, Yuan Li, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Zubair Afzal, Zenan Zhai, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor:
ChEMU 2021: Reaction Reference Resolution and Anaphora Resolution in Chemical Patents. ECIR (2) 2021: 608-615 - [c148]Shivashankar Subramanian, Afshin Rahimi, Timothy Baldwin, Trevor Cohn, Lea Frermann:
Fairness-aware Class Imbalanced Learning. EMNLP (1) 2021: 2045-2051 - [c147]Shivashankar Subramanian, Xudong Han, Timothy Baldwin, Trevor Cohn, Lea Frermann:
Evaluating Debiasing Techniques for Intersectional Biases. EMNLP (1) 2021: 2492-2498 - [c146]Chang Xu, Jun Wang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn:
Mitigating Data Poisoning in Text Classification with Differential Privacy. EMNLP (Findings) 2021: 4348-4356 - [c145]Jinming Zhao, Philip Arthur, Gholamreza Haffari, Trevor Cohn, Ehsan Shareghi:
It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data. EMNLP (1) 2021: 6707-6715 - [c144]Jiuzhou Han, Daniel Beck, Trevor Cohn:
Generating Diverse Descriptions from Semantic Graphs. INLG 2021: 1-11 - [c143]Fan Jiang, Trevor Cohn:
Incorporating Syntax and Semantics in Coreference Resolution with Heterogeneous Graph Attention Network. NAACL-HLT 2021: 1584-1591 - [c142]Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Andrew Turpin, Lea Frermann:
Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames. NAACL-HLT 2021: 2154-2166 - [c141]Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn:
PTST-UoM at SemEval-2021 Task 10: Parsimonious Transfer for Sequence Tagging. SemEval@ACL/IJCNLP 2021: 445-451 - [c140]Hung-Thinh Truong, Yulia Otmakhova, Timothy Baldwin, Jey Han Lau, Trevor Cohn, Karin Verspoor, Rahmad Mahendra, Lawrence Cavedon, Damiano Spina:
ITTC @ TREC 2021 Clinical Trials Track. TREC 2021 - [c139]Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn:
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning. WWW 2021: 3638-3650 - [i65]Xudong Han, Timothy Baldwin, Trevor Cohn:
Diverse Adversaries for Mitigating Bias in Training. CoRR abs/2101.10001 (2021) - [i64]Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn:
PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation. CoRR abs/2101.11216 (2021) - [i63]Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Andrew Turpin, Lea Frermann:
Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames. CoRR abs/2104.11030 (2021) - [i62]Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn:
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. CoRR abs/2107.05243 (2021) - [i61]Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn:
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. CoRR abs/2107.08357 (2021) - [i60]Jiuzhou Han, Daniel Beck, Trevor Cohn:
Generating Diverse Descriptions from Semantic Graphs. CoRR abs/2108.05659 (2021) - [i59]Xudong Han, Timothy Baldwin, Trevor Cohn:
Balancing out Bias: Achieving Fairness Through Training Reweighting. CoRR abs/2109.08253 (2021) - [i58]Chunhua Liu, Trevor Cohn, Lea Frermann:
Commonsense Knowledge in Word Associations and ConceptNet. CoRR abs/2109.09309 (2021) - [i57]Shivashankar Subramanian, Xudong Han, Timothy Baldwin, Trevor Cohn, Lea Frermann:
Evaluating Debiasing Techniques for Intersectional Biases. CoRR abs/2109.10441 (2021) - [i56]Shivashankar Subramanian, Afshin Rahimi, Timothy Baldwin, Trevor Cohn, Lea Frermann:
Fairness-aware Class Imbalanced Learning. CoRR abs/2109.10444 (2021) - [i55]Aili Shen, Xudong Han, Trevor Cohn, Timothy Baldwin, Lea Frermann:
Contrastive Learning for Fair Representations. CoRR abs/2109.10645 (2021) - [i54]Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn:
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source Data. CoRR abs/2110.03866 (2021) - [i53]Jinming Zhao, Philip Arthur, Gholamreza Haffari, Trevor Cohn, Ehsan Shareghi:
It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data. CoRR abs/2110.05213 (2021) - [i52]Zhuohan Xie, Trevor Cohn, Jey Han Lau:
Exploring Story Generation with Multi-task Objectives in Variational Autoencoders. CoRR abs/2111.08133 (2021) - 2020
- [c138]Nitika Mathur, Timothy Baldwin, Trevor Cohn:
Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics. ACL 2020: 4984-4997 - [c137]Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor:
Overview of ChEMU 2020: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents. CLEF 2020: 237-254 - [c136]Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Jingqi Wang, Yuankai Ren, Zhi Zhang, Yaoyun Zhang, Mai Hoang Dao, Pedro Ruas, Andre Lamurias, Francisco M. Couto, Jenny Copara, Nona Naderi, Julien Knafou, Patrick Ruch, Douglas Teodoro, Daniel M. Lowe, John Mayfield, Abdullatif Köksal, Hilal Dönmez, Elif Özkirimli, Arzucan Özgür, Darshini Mahendran, Gabrielle Gurdin, Nastassja Lewinski, Christina Tang, Bridget T. McInnes, C. S. Malarkodi, Pattabhi Rk Rao, Sobha Lalitha Devi, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor:
An Extended Overview of the CLEF 2020 ChEMU Lab: Information Extraction of Chemical Reactions from Patents. CLEF (Working Notes) 2020 - [c135]Dat Quoc Nguyen, Zenan Zhai, Hiyori Yoshikawa, Biaoyan Fang, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Saber A. Akhondi, Trevor Cohn, Timothy Baldwin, Karin Verspoor:
ChEMU: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents. ECIR (2) 2020: 572-579 - [c134]Najam Zaidi, Trevor Cohn, Gholamreza Haffari:
Decoding As Dynamic Programming For Recurrent Autoregressive Models. ICLR 2020 - [e3]Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-60-6 [contents] - [e2]Trevor Cohn, Yulan He, Yang Liu:
Findings of the Association for Computational Linguistics: EMNLP 2020, Online Event, 16-20 November 2020. Findings of ACL EMNLP 2020, Association for Computational Linguistics 2020, ISBN 978-1-952148-90-3 [contents] - [i51]Philip Arthur, Trevor Cohn, Gholamreza Haffari:
Learning Coupled Policies for Simultaneous Machine Translation. CoRR abs/2002.04306 (2020) - [i50]Nitika Mathur, Tim Baldwin, Trevor Cohn:
Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics. CoRR abs/2006.06264 (2020) - [i49]Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn:
Targeted Poisoning Attacks on Black-Box Neural Machine Translation. CoRR abs/2011.00675 (2020)
2010 – 2019
- 2019
- [j12]Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Arkaitz Zubiaga, Maria Liakata, Rob Procter:
Gaussian Processes for Rumour Stance Classification in Social Media. ACM Trans. Inf. Syst. 37(2): 20:1-20:24 (2019) - [c133]Afshin Rahimi, Yuan Li, Trevor Cohn:
Massively Multilingual Transfer for NER. ACL (1) 2019: 151-164 - [c132]Yitong Li, Timothy Baldwin, Trevor Cohn:
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference. ACL (1) 2019: 1923-1934 - [c131]Nitika Mathur, Timothy Baldwin, Trevor Cohn:
Putting Evaluation in Context: Contextual Embeddings Improve Machine Translation Evaluation. ACL (1) 2019: 2799-2808 - [c130]Zhuohan Xie, Jey Han Lau, Trevor Cohn:
From Shakespeare to Li-Bai: Adapting a Sonnet Model to Chinese Poetry. ALTA 2019: 10-18 - [c129]Zenan Zhai, Dat Quoc Nguyen, Saber A. Akhondi, Camilo Thorne, Christian Druckenbrodt, Trevor Cohn, Michelle Gregory, Karin Verspoor:
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings. BioNLP@ACL 2019: 328-338 - [c128]Dalin Wang, Daniel Beck, Trevor Cohn:
On the Role of Scene Graphs in Image Captioning. LANTERN@EMNLP-IJCNLP 2019: 29-34 - [c127]Xudong Han, Philip Schulz, Trevor Cohn:
Grounding learning of modifier dynamics: An application to color naming. EMNLP/IJCNLP (1) 2019: 1488-1493 - [c126]Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin:
Deep Ordinal Regression for Pledge Specificity Prediction. EMNLP/IJCNLP (1) 2019: 1729-1740 - [c125]Steven Spratley, Daniel Beck, Trevor Cohn:
A Unified Neural Architecture for Instrumental Audio Tasks. ICASSP 2019: 461-465 - [c124]Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn:
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing. ICML 2019: 3886-3895 - [c123]Ekaterina Vylomova, Ryan Cotterell, Trevor Cohn, Timothy Baldwin, Jason Eisner:
Contextualization of Morphological Inflection. NAACL-HLT (1) 2019: 2018-2024 - [c122]Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin:
Target Based Speech Act Classification in Political Campaign Text. *SEM@NAACL-HLT 2019: 273-282 - [c121]Daniel Beck, Trevor Cohn, Gholamreza Haffari:
Neural Speech Translation using Lattice Transformations and Graph Networks. TextGraphs@EMNLP 2019: 26-31 - [c120]Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn:
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. WWW 2019: 1028-1038 - [i48]Afshin Rahimi, Yuan Li, Trevor Cohn:
Multilingual NER Transfer for Low-resource Languages. CoRR abs/1902.00193 (2019) - [i47]Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn:
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. CoRR abs/1902.08918 (2019) - [i46]Steven Spratley, Daniel Beck, Trevor Cohn:
A Unified Neural Architecture for Instrumental Audio Tasks. CoRR abs/1903.00142 (2019) - [i45]Ekaterina Vylomova, Ryan Cotterell, Timothy Baldwin, Trevor Cohn, Jason Eisner:
Contextualization of Morphological Inflection. CoRR abs/1905.01420 (2019) - [i44]Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin:
Target Based Speech Act Classification in Political Campaign Text. CoRR abs/1905.07856 (2019) - [i43]Yitong Li, Timothy Baldwin, Trevor Cohn:
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference. CoRR abs/1906.02897 (2019) - [i42]Zenan Zhai, Dat Quoc Nguyen, Saber A. Akhondi, Camilo Thorne, Christian Druckenbrodt, Trevor Cohn, Michelle Gregory, Karin Verspoor:
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings. CoRR abs/1907.02679 (2019) - [i41]Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin:
Deep Ordinal Regression for Pledge Specificity Prediction. CoRR abs/1909.00187 (2019) - [i40]Xudong Han, Philip Schulz, Trevor Cohn:
Grounding learning of modifier dynamics: An application to color naming. CoRR abs/1909.07586 (2019) - 2018
- [j11]Nagesh Panyam Chandrasekarasastry, Karin Verspoor, Trevor Cohn, Kotagiri Ramamohanarao:
Exploiting graph kernels for high performance biomedical relation extraction. J. Biomed. Semant. 9(1): 7:1-7:11 (2018) - [j10]Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein:
Discourse-aware rumour stance classification in social media using sequential classifiers. Inf. Process. Manag. 54(2): 273-290 (2018) - [c119]Yitong Li, Timothy Baldwin, Trevor Cohn:
Towards Robust and Privacy-preserving Text Representations. ACL (2) 2018: 25-30 - [c118]Shivashankar Subramanian, Timothy Baldwin, Trevor Cohn:
Content-based Popularity Prediction of Online Petitions Using a Deep Regression Model. ACL (2) 2018: 182-188 - [c117]Daniel Beck, Gholamreza Haffari, Trevor Cohn:
Graph-to-Sequence Learning using Gated Graph Neural Networks. ACL (1) 2018: 273-283 - [c116]