Structured Adversarial Synthesis: A Multi-Agent Framework for Generating Persuasive Financial Analysis from Earnings Call Transcripts

Saisab Sadhu, Biswajit Patra, Tannay Basu


Anthology ID:
2025.finnlp-2.21
Volume:
Proceedings of The 10th Workshop on Financial Technology and Natural Language Processing
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Chung-Chi Chen, Genta Indra Winata, Stephen Rawls, Anirban Das, Hsin-Hsi Chen, Hiroya Takamura
Venue:
FinNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
283–291
Language:
URL:
https://preview.aclanthology.org/ingest-emnlp/2025.finnlp-2.21/
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Bibkey:
Cite (ACL):
Saisab Sadhu, Biswajit Patra, and Tannay Basu. 2025. Structured Adversarial Synthesis: A Multi-Agent Framework for Generating Persuasive Financial Analysis from Earnings Call Transcripts. In Proceedings of The 10th Workshop on Financial Technology and Natural Language Processing, pages 283–291, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Structured Adversarial Synthesis: A Multi-Agent Framework for Generating Persuasive Financial Analysis from Earnings Call Transcripts (Sadhu et al., FinNLP 2025)
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PDF:
https://preview.aclanthology.org/ingest-emnlp/2025.finnlp-2.21.pdf