@inproceedings{marti-alnuaimi-2026-adml,
title = "{ADML} at the {F}in{E}val 2026: Version-Aware Retrieval and Grounded Sparse Editing for Multilingual Financial {QA}",
author = "Marti, Gautier and
AlNuaimi, Khaled",
editor = "Huang, Jimin and
Lee, Yongjae and
Ananiadou, Sophia and
Chen, Hsin-Hsi and
Takamura, Hiroya and
Chen, Chung-Chi",
booktitle = "Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.finnlp-1.65/",
pages = "750--754",
ISBN = "979-8-89176-466-8",
abstract = "We present ADML{'}s second-place system for the FinEval 2026 PolyFiQA subtask. PolyFiQA requires concise answers grounded jointly in financial statements and contemporaneous news in five languages. We developed a deterministic fact compiler with strict number provenance, schema-specific realization, a 100-word budget, and a sparse answer-edit lattice. All 76 released test queries exactly matched queries in the public PolyFiQA-Expert-July snapshot released in July 2025. Under the organizer{'}s external-data policy, our selected lane retrieved only exact or conservatively normalized full-query references and capped them without rephrasing. It scored 0.9994 public ROUGE-1 F1 but 0.3726 privately, ranking second. The sharp split exposes reference-version shift: input identity and historical answer identity held publicly but not privately. Historical leave-company-out experiments similarly show that answer-oracle headroom is easy to construct but difficult to route safely. We argue for version-aware retrieval and abstaining grounded fallbacks rather than unconditional reference reuse."
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<abstract>We present ADML’s second-place system for the FinEval 2026 PolyFiQA subtask. PolyFiQA requires concise answers grounded jointly in financial statements and contemporaneous news in five languages. We developed a deterministic fact compiler with strict number provenance, schema-specific realization, a 100-word budget, and a sparse answer-edit lattice. All 76 released test queries exactly matched queries in the public PolyFiQA-Expert-July snapshot released in July 2025. Under the organizer’s external-data policy, our selected lane retrieved only exact or conservatively normalized full-query references and capped them without rephrasing. It scored 0.9994 public ROUGE-1 F1 but 0.3726 privately, ranking second. The sharp split exposes reference-version shift: input identity and historical answer identity held publicly but not privately. Historical leave-company-out experiments similarly show that answer-oracle headroom is easy to construct but difficult to route safely. We argue for version-aware retrieval and abstaining grounded fallbacks rather than unconditional reference reuse.</abstract>
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%0 Conference Proceedings
%T ADML at the FinEval 2026: Version-Aware Retrieval and Grounded Sparse Editing for Multilingual Financial QA
%A Marti, Gautier
%A AlNuaimi, Khaled
%Y Huang, Jimin
%Y Lee, Yongjae
%Y Ananiadou, Sophia
%Y Chen, Hsin-Hsi
%Y Takamura, Hiroya
%Y Chen, Chung-Chi
%S Proceedings of the 11th Workshop on Financial Technology and Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-466-8
%F marti-alnuaimi-2026-adml
%X We present ADML’s second-place system for the FinEval 2026 PolyFiQA subtask. PolyFiQA requires concise answers grounded jointly in financial statements and contemporaneous news in five languages. We developed a deterministic fact compiler with strict number provenance, schema-specific realization, a 100-word budget, and a sparse answer-edit lattice. All 76 released test queries exactly matched queries in the public PolyFiQA-Expert-July snapshot released in July 2025. Under the organizer’s external-data policy, our selected lane retrieved only exact or conservatively normalized full-query references and capped them without rephrasing. It scored 0.9994 public ROUGE-1 F1 but 0.3726 privately, ranking second. The sharp split exposes reference-version shift: input identity and historical answer identity held publicly but not privately. Historical leave-company-out experiments similarly show that answer-oracle headroom is easy to construct but difficult to route safely. We argue for version-aware retrieval and abstaining grounded fallbacks rather than unconditional reference reuse.
%U https://aclanthology.org/2026.finnlp-1.65/
%P 750-754
Markdown (Informal)
[ADML at the FinEval 2026: Version-Aware Retrieval and Grounded Sparse Editing for Multilingual Financial QA](https://aclanthology.org/2026.finnlp-1.65/) (Marti & AlNuaimi, FinNLP 2026)
ACL