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Hiroki Sakaji

4 papers hereh-index 14 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.MA2
same name
  • Hiroki Sakaji — 15 papers, h 15
  • Hiroki Sakaji — 3 papers, h 1
  • Hiroki Sakaji — 2 papers, h 2
  • Hiroki Sakaji — 2 papers, h 1
  • Hiroki Sakaji — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedEnhancing Financial Domain Adaptation of Language Models via Model Augmentation

3 citations · 3 across the 4 of their papers we have counts for

collaborators

4 papers

cs.MA2026

Dynamic Haven Selection for Multi-Agent Pickup and Delivery in Constrained Warehouses

Taisei Hirayama, Kohei Yoshida, Hiroki Sakaji +1

Space-efficient warehouse layouts often contain single-agent-width aisles and dead-end workstations where robots have few places to wait without blocking others. In Multi-Agent Pic…

cs.MA2026

Fixed-Haven Reservation for Online Multi-Agent Pickup and Delivery in Dense Warehouses

Taisei Hirayama, Kohei Yoshida, Hiroki Sakaji +1

Dense warehouses often contain single-lane aisles, dead ends, and tree-like guidepaths that leave little room for idle agents to wait without blocking others. Existing Multi-Agent…

cs.CL2024

Indexing Economic Fluctuation Narratives from Keiki Watchers Survey

Eriko Shigetsugu, Hiroki Sakaji, Itsuki Noda

In this paper, we design indices of economic fluctuation narratives derived from economic surveys. Companies, governments, and investors rely on key metrics like GDP and industrial…

cs.CL2024★ 3 cited

Enhancing Financial Domain Adaptation of Language Models via Model Augmentation

Kota Tanabe, Masanori Hirano, Kazuki Matoya +3

The domain adaptation of language models, including large language models (LLMs), has become increasingly important as the use of such models continues to expand. This study demons…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.