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ORCIDDanushka Bollegala
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2020 – today
- 2024
[j26]Yang Zhao
, Danushka Bollegala, Shunsuke Hirose, Yingzi Jin, Tomotake Kozu:
Community knowledge graph abstraction for enhanced link prediction: A study on PubMed knowledge graph. J. Biomed. Informatics 158: 104725 (2024)- [j25]Guanqun Cao, Jiaqi Jiang, Danushka Bollegala, Min Li, Shan Luo:
Multimodal zero-shot learning for tactile texture recognition. Robotics Auton. Syst. 176: 104688 (2024) - [c143]Junjie Chen, Xiangheng He, Danushka Bollegala, Yusuke Miyao:
Unsupervised Parsing by Searching for Frequent Word Sequences among Sentences with Equivalent Predicate-Argument Structures. ACL (Findings) 2024: 3760-3772 - [c142]Taichi Aida, Danushka Bollegala:
A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection. ACL (Findings) 2024: 7570-7584 - [c141]Gaifan Zhang, Yi Zhou, Danushka Bollegala:
Evaluating Unsupervised Dimensionality Reduction Methods for Pretrained Sentence Embeddings. LREC/COLING 2024: 6530-6543 - [c140]Daisuke Oba, Masahiro Kaneko, Danushka Bollegala:
In-Contextual Gender Bias Suppression for Large Language Models. EACL (Findings) 2024: 1722-1742 - [c139]Tianhui Zhang, Bei Peng, Danushka Bollegala:
Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning. EMNLP (Findings) 2024: 9226-9242 - [c138]Yi Zhou, Danushka Bollegala, José Camacho-Collados:
Evaluating Short-Term Temporal Fluctuations of Social Biases in Social Media Data and Masked Language Models. EMNLP 2024: 19693-19708 - [c137]Micheal Abaho, Danushka Bollegala, Gary Leeming, Dan W. Joyce, Iain E. Buchan:
Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER. NAACL-HLT 2024: 5013-5029 - [c136]Procheta Sen, Tulika Saha, Danushka Bollegala:
Report on the 2nd Symposium on NLP for Social Good. NSG 2024 - [e3]Procheta Sen, Tulika Saha, Danushka Bollegala:
Proceedings of the 2nd Symposium on NLP for Social Good (NSG 2024), Liverpool, United Kingdom, April 25-26, 2024. CEUR Workshop Proceedings 3764, CEUR-WS.org 2024 [contents] - [i82]Masahiro Kaneko, Danushka Bollegala, Timothy Baldwin:
The Gaps between Pre-train and Downstream Settings in Bias Evaluation and Debiasing. CoRR abs/2401.08511 (2024) - [i81]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki, Timothy Baldwin:
Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting. CoRR abs/2401.15585 (2024) - [i80]Masahiro Kaneko, Danushka Bollegala, Timothy Baldwin:
Eagle: Ethical Dataset Given from Real Interactions. CoRR abs/2402.14258 (2024) - [i79]Taichi Aida, Danushka Bollegala:
A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection. CoRR abs/2403.00226 (2024) - [i78]Gaifan Zhang, Yi Zhou, Danushka Bollegala:
Evaluating Unsupervised Dimensionality Reduction Methods for Pretrained Sentence Embeddings. CoRR abs/2403.14001 (2024) - [i77]Micheal Abaho, Danushka Bollegala, Gary Leeming, Dan W. Joyce, Iain E. Buchan:
Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER. CoRR abs/2403.18025 (2024) - [i76]Junjie Chen, Xiangheng He, Danushka Bollegala, Yusuke Miyao:
Constituents Correspond to Word Sequence Patterns among Sentences with Equivalent Predicate-Argument Structures: Unsupervised Constituency Parsing by Span Matching. CoRR abs/2404.12059 (2024) - [i75]Tianhui Zhang, Bei Peng, Danushka Bollegala:
Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning. CoRR abs/2404.16807 (2024) - [i74]Yi Zhou, Danushka Bollegala, José Camacho-Collados:
Evaluating Short-Term Temporal Fluctuations of Social Biases in Social Media Data and Masked Language Models. CoRR abs/2406.13556 (2024) - [i73]Taichi Aida, Danushka Bollegala:
Investigating the Contextualised Word Embedding Dimensions Responsible for Contextual and Temporal Semantic Changes. CoRR abs/2407.02820 (2024) - [i72]Junjie Chen, Xiangheng He, Yusuke Miyao, Danushka Bollegala:
Improving Unsupervised Constituency Parsing via Maximizing Semantic Information. CoRR abs/2410.02558 (2024) - 2023
- [j24]Procheta Sen, Tulika Saha, Danushka Bollegala:
Report on the 1st Symposium on NLP for Social: Good (NSG 2023). SIGIR Forum 57(2): 7:1-7:9 (2023) - [c135]Haochen Luo, Yi Zhou, Danushka Bollegala:
Together We Make Sense-Learning Meta-Sense Embeddings. ACL (Findings) 2023: 2638-2651 - [c134]Taichi Aida, Danushka Bollegala:
Unsupervised Semantic Variation Prediction using the Distribution of Sibling Embeddings. ACL (Findings) 2023: 6868-6882 - [c133]Saeth Wannasuphoprasit, Yi Zhou, Danushka Bollegala:
Solving Cosine Similarity Underestimation between High Frequency Words by \ell₂ Norm Discounting. ACL (Findings) 2023: 8644-8652 - [c132]Xiaohang Tang, Yi Zhou, Danushka Bollegala:
Learning Dynamic Contextualised Word Embeddings via Template-based Temporal Adaptation. ACL (1) 2023: 9352-9369 - [c131]Yoichi Ishibashi, Danushka Bollegala, Katsuhito Sudoh, Satoshi Nakamura:
Evaluating the Robustness of Discrete Prompts. EACL 2023: 2365-2376 - [c130]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Comparing Intrinsic Gender Bias Evaluation Measures without using Human Annotated Examples. EACL 2023: 2849-2855 - [c129]Xiaohang Tang, Yi Zhou, Taichi Aida, Procheta Sen, Danushka Bollegala:
A Word Sense Distribution-based approach for Semantic Change Prediction. EMNLP (Findings) 2023: 3575-3590 - [c128]Taichi Aida, Danushka Bollegala:
Swap and Predict - Predicting the Semantic Changes in Words across Corpora by Context Swapping. EMNLP (Findings) 2023: 7753-7772 - [c127]Yi Zhou, José Camacho-Collados, Danushka Bollegala:
A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models. EMNLP 2023: 11082-11100 - [c126]Guanqun Cao, Jiaqi Jiang, Ningtao Mao, Danushka Bollegala, Min Li, Shan Luo:
Vis2Hap: Vision-based Haptic Rendering by Cross-modal Generation. ICRA 2023: 12443-12449 - [c125]Tianhui Zhang, Danushka Bollegala, Bei Peng:
Learning to Predict Concept Ordering for Common Sense Generation. IJCNLP (2) 2023: 10-19 - [c124]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
The Impact of Debiasing on the Performance of Language Models in Downstream Tasks is Underestimated. IJCNLP (2) 2023: 29-36 - [c123]Danushka Bollegala, Shuichi Otake, Tomoya Machide, Ken-ichi Kawarabayashi:
A Neighbourhood-Aware Differential Privacy Mechanism for Static Word Embeddings. IJCNLP (Findings) 2023: 65-79 - [c122]Guanqun Cao, Jiaqi Jiang, Danushka Bollegala, Shan Luo:
Learn from Incomplete Tactile Data: Tactile Representation Learning with Masked Autoencoders. IROS 2023: 10800-10805 - [e2]Danushka Bollegala, Ruihong Huang, Alan Ritter:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, ACL 2023, Toronto, Canada, July 10-12, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-70-8 [contents] - [i71]Guanqun Cao, Jiaqi Jiang, Ningtao Mao, Danushka Bollegala, Min Li, Shan Luo:
Vis2Hap: Vision-based Haptic Rendering by Cross-modal Generation. CoRR abs/2301.06826 (2023) - [i70]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Comparing Intrinsic Gender Bias Evaluation Measures without using Human Annotated Examples. CoRR abs/2301.12074 (2023) - [i69]Yoichi Ishibashi, Danushka Bollegala, Katsuhito Sudoh, Satoshi Nakamura:
Evaluating the Robustness of Discrete Prompts. CoRR abs/2302.05619 (2023) - [i68]Taichi Aida, Danushka Bollegala:
Unsupervised Semantic Variation Prediction using the Distribution of Sibling Embeddings. CoRR abs/2305.08654 (2023) - [i67]Saeth Wannasuphoprasit, Yi Zhou, Danushka Bollegala:
Solving Cosine Similarity Underestimation between High Frequency Words by L2 Norm Discounting. CoRR abs/2305.10610 (2023) - [i66]Samantha Durdy, Michael W. Gaultois, Vladimir V. Gusev, Danushka Bollegala, Matthew J. Rosseinsky:
Metrics for quantifying isotropy in high dimensional unsupervised clustering tasks in a materials context. CoRR abs/2305.16372 (2023) - [i65]Haochen Luo, Yi Zhou, Danushka Bollegala:
Together We Make Sense - Learning Meta-Sense Embeddings from Pretrained Static Sense Embeddings. CoRR abs/2305.19092 (2023) - [i64]Guanqun Cao, Jiaqi Jiang, Danushka Bollegala, Min Li, Shan Luo:
Multimodal Zero-Shot Learning for Tactile Texture Recognition. CoRR abs/2306.12705 (2023) - [i63]Guanqun Cao, Jiaqi Jiang, Danushka Bollegala, Shan Luo:
Learn from Incomplete Tactile Data: Tactile Representation Learning with Masked Autoencoders. CoRR abs/2307.07358 (2023) - [i62]Tianhui Zhang, Danushka Bollegala, Bei Peng:
Learning to Predict Concept Ordering for Common Sense Generation. CoRR abs/2309.06363 (2023) - [i61]Daisuke Oba, Masahiro Kaneko, Danushka Bollegala:
In-Contextual Bias Suppression for Large Language Models. CoRR abs/2309.07251 (2023) - [i60]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
The Impact of Debiasing on the Performance of Language Models in Downstream Tasks is Underestimated. CoRR abs/2309.09092 (2023) - [i59]Danushka Bollegala, Shuichi Otake, Tomoya Machide, Ken-ichi Kawarabayashi:
A Neighbourhood-Aware Differential Privacy Mechanism for Static Word Embeddings. CoRR abs/2309.10551 (2023) - [i58]Taichi Aida, Danushka Bollegala:
Swap and Predict - Predicting the Semantic Changes in Words across Corpora by Context Swapping. CoRR abs/2310.10397 (2023) - [i57]Xiaohang Tang, Yi Zhou, Taichi Aida, Procheta Sen, Danushka Bollegala:
Can Word Sense Distribution Detect Semantic Changes of Words? CoRR abs/2310.10400 (2023) - [i56]Yi Zhou, José Camacho-Collados, Danushka Bollegala:
A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models. CoRR abs/2310.12936 (2023) - 2022
- [j23]Tadashi Tsubota, Danushka Bollegala, Yang Zhao, Yingzi Jin, Tomotake Kozu:
Improvement of intervention information detection for automated clinical literature screening during systematic review. J. Biomed. Informatics 134: 104185 (2022) - [c121]Masahiro Kaneko, Danushka Bollegala:
Unmasking the Mask - Evaluating Social Biases in Masked Language Models. AAAI 2022: 11954-11962 - [c120]Yi Zhou, Masahiro Kaneko, Danushka Bollegala:
Sense Embeddings are also Biased - Evaluating Social Biases in Static and Contextualised Sense Embeddings. ACL (1) 2022: 1924-1935 - [c119]Micheal Abaho, Danushka Bollegala, Paula Williamson, Susanna Dodd:
Position-based Prompting for Health Outcome Generation. BioNLP@ACL 2022: 26-36 - [c118]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Debiasing Isn't Enough! - on the Effectiveness of Debiasing MLMs and Their Social Biases in Downstream Tasks. COLING 2022: 1299-1310 - [c117]Yi Zhou, Danushka Bollegala:
On the Curious Case of l2 norm of Sense Embeddings. EMNLP (Findings) 2022: 2593-2602 - [c116]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Gender Bias in Meta-Embeddings. EMNLP (Findings) 2022: 3118-3133 - [c115]Danushka Bollegala:
Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings. IJCAI 2022: 4058-4064 - [c114]Danushka Bollegala, James O'Neill:
A Survey on Word Meta-Embedding Learning. IJCAI 2022: 5402-5409 - [c113]Danushka Bollegala, Tomoya Machide, Ken-ichi Kawarabayashi:
Query Obfuscation by Semantic Decomposition. LREC 2022: 6200-6211 - [c112]Keigo Takahashi, Danushka Bollegala:
Unsupervised Attention-based Sentence-Level Meta-Embeddings from Contextualised Language Models. LREC 2022: 7155-7163 - [c111]Masahiro Kaneko, Aizhan Imankulova, Danushka Bollegala, Naoaki Okazaki:
Gender Bias in Masked Language Models for Multiple Languages. NAACL-HLT 2022: 2740-2750 - [c110]Huda Hakami, Mona Hakami, Angrosh Mandya, Danushka Bollegala:
Learning to Borrow- Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion. NAACL-HLT 2022: 2887-2898 - [i55]Micheal Abaho, Danushka Bollegala, Paula R. Williamson, Susanna Dodd:
Assessment of contextualised representations in detecting outcome phrases in clinical trials. CoRR abs/2203.03547 (2022) - [i54]Yi Zhou, Masahiro Kaneko, Danushka Bollegala:
Sense Embeddings are also Biased-Evaluating Social Biases in Static and Contextualised Sense Embeddings. CoRR abs/2203.07523 (2022) - [i53]Micheal Abaho, Danushka Bollegala, Paula Williamson, Susanna Dodd:
Position-based Prompting for Health Outcome Generation. CoRR abs/2204.03489 (2022) - [i52]Keigo Takahashi, Danushka Bollegala:
Unsupervised Attention-based Sentence-Level Meta-Embeddings from Contextualised Language Models. CoRR abs/2204.07746 (2022) - [i51]Danushka Bollegala, James O'Neill:
A Survey on Word Meta-Embedding Learning. CoRR abs/2204.11660 (2022) - [i50]Danushka Bollegala:
Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings. CoRR abs/2204.12386 (2022) - [i49]Huda Hakami, Mona Hakami, Angrosh Mandya, Danushka Bollegala:
Learning to Borrow - Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion. CoRR abs/2204.13097 (2022) - [i48]Masahiro Kaneko, Aizhan Imankulova, Danushka Bollegala, Naoaki Okazaki:
Gender Bias in Masked Language Models for Multiple Languages. CoRR abs/2205.00551 (2022) - [i47]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Gender Bias in Meta-Embeddings. CoRR abs/2205.09867 (2022) - [i46]Samantha Durdy, Michael W. Gaultois, Vladimir V. Gusev, Danushka Bollegala, Matthew J. Rosseinsky:
Random projections and Kernelised Leave One Cluster Out Cross-Validation: Universal baselines and evaluation tools for supervised machine learning for materials properties. CoRR abs/2206.08841 (2022) - [i45]Xiaohang Tang, Yi Zhou, Danushka Bollegala:
Learning Dynamic Contextualised Word Embeddings via Template-based Temporal Adaptation. CoRR abs/2208.10734 (2022) - [i44]Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki:
Debiasing isn't enough! - On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks. CoRR abs/2210.02938 (2022) - [i43]Yi Zhou, Danushka Bollegala:
On the Curious Case of 𝓁2 norm of Sense Embeddings. CoRR abs/2210.14815 (2022) - 2021
- [j22]Masaru Isonuma, Junichiro Mori, Danushka Bollegala, Ichiro Sakata:
Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance. Trans. Assoc. Comput. Linguistics 9: 945-961 (2021) - [c109]Iqra Muhammad, Danushka Bollegala, Frans Coenen, Carrol Gamble, Anna Kearney, Paula Williamson:
Document Ranking for Curated Document Databases Using BERT and Knowledge Graph Embeddings: Introducing GRAB-Rank. DaWaK 2021: 116-127 - [c108]Masahiro Kaneko, Danushka Bollegala:
Dictionary-based Debiasing of Pre-trained Word Embeddings. EACL 2021: 212-223 - [c107]Masahiro Kaneko, Danushka Bollegala:
Debiasing Pre-trained Contextualised Embeddings. EACL 2021: 1256-1266 - [c106]Danushka Bollegala, Huda Hakami, Yuichi Yoshida, Ken-ichi Kawarabayashi:
RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding. EACL 2021: 1551-1565 - [c105]James O'Neill, Polina Rozenshtein, Ryuichi Kiryo, Motoko Kubota, Danushka Bollegala:
I Wish I Would Have Loved This One, But I Didn't - A Multilingual Dataset for Counterfactual Detection in Product Review. EMNLP (1) 2021: 7092-7108 - [c104]Micheal Abaho, Danushka Bollegala, Paula Williamson, Susanna Dodd:
Detect and Classify - Joint Span Detection and Classification for Health Outcomes. EMNLP (1) 2021: 8709-8721 - [c103]Danushka Bollegala, Yi Zhou:
Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy. PACLIC 2021: 493-502 - [c102]Mikhail Fain, Niall Twomey, Danushka Bollegala:
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora. SIGIR 2021: 2106-2110 - [i42]James O'Neill, Danushka Bollegala:
k-Neighbor Based Curriculum Sampling for Sequence Prediction. CoRR abs/2101.09313 (2021) - [i41]Masahiro Kaneko, Danushka Bollegala:
Debiasing Pre-trained Contextualised Embeddings. CoRR abs/2101.09523 (2021) - [i40]Masahiro Kaneko, Danushka Bollegala:
Dictionary-based Debiasing of Pre-trained Word Embeddings. CoRR abs/2101.09525 (2021) - [i39]Danushka Bollegala, Huda Hakami, Yuichi Yoshida, Ken-ichi Kawarabayashi:
RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding. CoRR abs/2101.10070 (2021) - [i38]James O'Neill, Danushka Bollegala:
Semantically-Conditioned Negative Samples for Efficient Contrastive Learning. CoRR abs/2102.06603 (2021) - [i37]James O'Neill, Polina Rozenshtein, Ryuichi Kiryo, Motoko Kubota, Danushka Bollegala:
I Wish I Would Have Loved This One, But I Didn't - A Multilingual Dataset for Counterfactual Detection in Product Reviews. CoRR abs/2104.06893 (2021) - [i36]Masahiro Kaneko, Danushka Bollegala:
Unmasking the Mask - Evaluating Social Biases in Masked Language Models. CoRR abs/2104.07496 (2021) - [i35]Micheal Abaho, Danushka Bollegala, Paula Williamson, Susanna Dodd:
Detect and Classify - Joint Span Detection and Classification for Health Outcomes. CoRR abs/2104.07789 (2021) - [i34]Mikhail Fain, Niall Twomey, Danushka Bollegala:
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora. CoRR abs/2105.04971 (2021) - [i33]Masaru Isonuma, Junichiro Mori, Danushka Bollegala, Ichiro Sakata:
Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance. CoRR abs/2106.08007 (2021) - [i32]Yi Zhou, Danushka Bollegala:
Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy. CoRR abs/2110.02204 (2021) - 2020
- [j21]Katie Atkinson, Trevor J. M. Bench-Capon, Danushka Bollegala:
Explanation in AI and law: Past, present and future. Artif. Intell. 289: 103387 (2020) - [j20]Yash Khemchandani, Stephen O'Hagan, Soumitra Samanta, Neil Swainston, Timothy J. Roberts, Danushka Bollegala, Douglas B. Kell:
DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach. J. Cheminformatics 12(1): 53 (2020) - [c101]Masaru Isonuma, Junichiro Mori, Danushka Bollegala, Ichiro Sakata:
Tree-Structured Neural Topic Model. ACL 2020: 800-806 - [c100]Masahiro Kaneko, Danushka Bollegala:
Autoencoding Improves Pre-trained Word Embeddings. COLING 2020: 1699-1713 - [c99]Angrosh Mandya, Danushka Bollegala, Frans Coenen:
Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction. COLING 2020: 6424-6435 - [c98]James O'Neill, Danushka Bollegala:
Meta-Embedding as Auxiliary Task Regularization. ECAI 2020: 2124-2131 - [c97]Xia Cui, Danushka Bollegala:
Multi-Source Attention for Unsupervised Domain Adaptation. AACL/IJCNLP 2020: 873-883 - [c96]Guanqun Cao, Yi Zhou, Danushka Bollegala, Shan Luo:
Spatio-temporal Attention Model for Tactile Texture Recognition. IROS 2020: 9896-9902 - [c95]Angrosh Mandya, James O'Neill, Danushka Bollegala, Frans Coenen:
Do not let the history haunt you: Mitigating Compounding Errors in Conversational Question Answering. LREC 2020: 2017-2025 - [c94]Danushka Bollegala, Ryuichi Kiryo, Kosuke Tsujino, Haruki Yukawa:
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction. LREC 2020: 3851-3860 - [c93]Iqra Muhammad, Danushka Bollegala, Frans Coenen, Carrol Gamble, Anna Kearney, Paula Williamson:
Maintaining Curated Document Databases Using a Learning to Rank Model: The ORRCA Experience. SGAI Conf. 2020: 345-357 - [i31]Danushka Bollegala, Ryuichi Kiryo, Kosuke Tsujino, Haruki Yukawa:
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction. CoRR abs/2002.11004 (2020) - [i30]Xia Cui, Danushka Bollegala:
Multi-source Attention for Unsupervised Domain Adaptation. CoRR abs/2004.06608 (2020) - [i29]Angrosh Mandya, Danushka Bollegala, Frans Coenen:
Contextualised Graph Attention for Improved Relation Extraction. CoRR abs/2004.10624 (2020) - [i28]Asir Saeed, Khai Mai, Pham Minh, Nguyen Tuan Duc, Danushka Bollegala:
Weakly-Supervised Neural Response Selection from an Ensemble of Task-Specialised Dialogue Agents. CoRR abs/2005.03066 (2020) - [i27]Angrosh Mandya, James O'Neill, Danushka Bollegala, Frans Coenen:
Do not let the history haunt you - Mitigating Compounding Errors in Conversational Question Answering. CoRR abs/2005.05754 (2020) - [i26]Guanqun Cao, Yi Zhou, Danushka Bollegala, Shan Luo:
Spatio-temporal Attention Model for Tactile Texture Recognition. CoRR abs/2008.04442 (2020) - [i25]Masahiro Kaneko, Danushka Bollegala:
Autoencoding Improves Pre-trained Word Embeddings. CoRR abs/2010.13094 (2020)
2010 – 2019
- 2019
- [c92]Masahiro Kaneko, Danushka Bollegala:
Gender-preserving Debiasing for Pre-trained Word Embeddings. ACL (1) 2019: 1641-1650 - [c91]Mohammed Alsuhaibani, Takanori Maehara, Danushka Bollegala:
Joint Learning of Hierarchical Word Embeddings from a Corpus and a Taxonomy. AKBC 2019 - [c90]Huda Hakami, Danushka Bollegala:
Learning Relation Representations from Word Representations. AKBC 2019 - [c89]Angrosh Mandya, Danushka Bollegala, Frans Coenen, Katie Atkinson:
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction. AKBC 2019 - [c88]