Relevant paper and code repository links
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Hi All,
We can post all the paper links here for helping each other and may be also express why that paper/code is important in the later stages.
Comparative argument retrieval paper links:
* Combined Approaches: {Mixed Methods}
- Mixed Approaches, identify bottlenecks for improvements. {Paper: 3, Code: 4}
- paper: http://ceur-ws.org/Vol-2936/paper-215.pdf, code: https://github.com/JanNiklasWeder/Touche-21-Task-2
* Pre-trained Language Models and NLU: {Important paper**}
- Seq2Seq, Transformer, and BERT embedding. {Paper: 3, Code: 4.5**}
- paper: http://ceur-ws.org/Vol-2696/paper_210.pdf, code: https://github.com/skoltech-nlp/touche
* DistilBERT-based Argumentation Retrieval: {Our Baseline Paper**}
- query expansion, argument extraction, scoring, and sorting + BERT {Paper: 4, Code: 1}
- paper: http://ceur-ws.org/Vol-2936/paper-209.pdf, code: https://github.com/jmriebold/BoilerPy3, https://github.com/adbar/trafilatura, https://github.com/UKPLab/sentence-transformers
* ensemble based retrieval methods + BERT re-ranking methodology:
- comparative argument touche {Paper: 3, Code: 2}
- paper: http://ceur-ws.org/Vol-2936/paper-211.pdf, code: https://github.com/Georgetown-IR-Lab/OpenNIR
* Search Engine Paper: Usage of whoosh and targer library {can be used to add intrepretability component at last stage}
- whoosh library usage for index creation: https://whoosh.readthedocs.io/en/latest/quickstart.html {Paper: 2, Code: 1}
- paper: http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_178.pdf, code: https://github.com/uhh-lt/targer
* Baseline paper approaches: http://ceur-ws.org/Vol-2696/paper_207.pdf
* Interesting Approach: http://ceur-ws.org/Vol-2696/paper_174.pdf
* [X] Not good code: https://github.com/touche-webis-de/gienapp21
Concepts Used:
https://github.com/touche-webis-de/weder21multi-stage
BERT ranker: https://arxiv.org/pdf/1910.14424.pdf
docT5query: https://github.com/castorini/docTTTTTquery
Document Query Expansion paper: https://arxiv.org/pdf/1904.08375.pdf
Here are some relevant papers and git hub repositories which I found
https://github.com/ahmad-Wattar/Websuche-und-Information-Retrieval
https://arxiv.org/abs/1901.05041
https://link.springer.com/article/10.1007/s13222-020-00346-8
https://aclanthology.org/W19-4516/
Query Expansion Methods discussion:
* Synonym and antonym generation method: {paper: http://ceur-ws.org/Vol-2936/paper-209.pdf, code: https://github.com/touche-webis-de/weder21/blob/main/src/preprocessing/QueryExpansion.py}
- We should use synonyms and antonyms of comparative quantities + noun alternative replacements for constructing alternative queries in CNF/DNF form.
* More relevant approach, Doc2Query expando-mono-duo design-pattern (H-1): {paper: https://arxiv.org/pdf/2101.05667.pdf, code: https://www.tira.io/t/expanded-passages-for-the-touche-22-task-2-argument-retrieval-for-comparative-questions/578, touche blog link: https://www.tira.io/t/expanded-passages-for-the-touche-22-task-2-argument-retrieval-for-comparative-questions/578}
- MS MACRO trained docT5queries are available for touche 22 documents, fine-tuning may be required for better performance (future work).
- Ideal SOTA design needs to be followed for the implementation.
Touche papers :
http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_130.pdf
https://www.uni-trier.de/fileadmin/fb4/prof/INF/DBI/Publikationen/sigir19_dumani_schenkel.pdf
http://ceur-ws.org/Vol-2936/paper-209.pdf !!
Toolkit:
https://github.com/castorini/anserini
Github:
https://github.com/sayankotor/touche
https://github.com/JanNiklasWeder/Touche-21-Task-2
Ideas from a workshop:
https://cs.uni-paderborn.de/fileadmin/informatik/fg/css/teaching/wachsmuth18-argumentation-retrieval-and-analysis.pdf
Papers that can be relevant for evaluation metrics:
* QMUL-SDS's "step-by-step" binary classification approach: https://github.com/XiaZeng0223/sciverbinary
* SCIFACT task and its evaluation metrics : https://arxiv.org/pdf/2004.14974.pdf
* VERT5ERINI System Approach: https://aclanthology.org/2021.louhi-1.11.pdf
Approaches are finalized, closing the issue!