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1
Query Expansion and Entity Weighting for Query Reformulation Retrieval in Voice Assistant Systems ...
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2
Improving Word Translation via Two-Stage Contrastive Learning ...
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3
Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction ...
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4
TURNER: The Uncertainty-based Retrieval Framework for Chinese NER ...
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5
LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval ...
Xu, Canwen; Guo, Daya; Duan, Nan. - : arXiv, 2022
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6
Personalized Transformer for Explainable Recommendation ...
Li, Lei; Zhang, Yongfeng; Chen, Li. - : arXiv, 2021
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7
Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings ...
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8
Leveraging Multilingual Transformers for Hate Speech Detection ...
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9
Multistage BiCross encoder for multilingual access to COVID-19 health information ...
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10
Scalable Cross-lingual Document Similarity through Language-specific Concept Hierarchies ...
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11
Revisiting Indirect Ontology Alignment : New Challenging Issues in Cross-Lingual Context ...
Kachroudi, Marouen. - : arXiv, 2021
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12
A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models ...
Abstract: Bangla -- ranked as the 6th most widely spoken language across the world (https://www.ethnologue.com/guides/ethnologue200), with 230 million native speakers -- is still considered as a low-resource language in the natural language processing (NLP) community. With three decades of research, Bangla NLP (BNLP) is still lagging behind mainly due to the scarcity of resources and the challenges that come with it. There is sparse work in different areas of BNLP; however, a thorough survey reporting previous work and recent advances is yet to be done. In this study, we first provide a review of Bangla NLP tasks, resources, and tools available to the research community; we benchmark datasets collected from various platforms for nine NLP tasks using current state-of-the-art algorithms (i.e., transformer-based models). We provide comparative results for the studied NLP tasks by comparing monolingual vs. multilingual models of varying sizes. We report our results using both individual and consolidated datasets and ... : Under Review, Bangla language processing, text classification, sequence tagging, datasets, benchmarks, transformer models ...
Keyword: 68T50; Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; I.2.7; Information Retrieval cs.IR; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.2107.03844
https://arxiv.org/abs/2107.03844
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13
Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages ...
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14
Ranking Facts for Explaining Answers to Elementary Science Questions ...
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15
Few-shot Named Entity Recognition with Cloze Questions ...
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16
Engineering Knowledge Graph from Patent Database ...
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17
SUper Team at SemEval-2016 Task 3: Building a feature-rich system for community question answering ...
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18
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models ...
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19
SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval ...
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20
Matching with Transformers in MELT ...
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