森下 皓文 Terufumi Morishita
日立製作所 中央研究所にて、主に自然言語処理の研究に従事しています。 日々の業務では実用化を見据えた研究を中心に進めつつ、以下のような研究テーマにも取り組んでいます:
- 大規模言語モデルの推論能力向上に向けた、論理推論コーパスの自動生成
- ビジネス観点に基づく事例検索を活用した、意思決定支援AI
- 自然言語処理分野の国際コンペティションへの参加
また、自然言語処理に限らず、関連分野の研究にも取り組んでいます:
- 機械学習基礎: アンサンブル学習の性能を決定づける根本要因の理論的解明
- 経済学x AI: 多数のLLMエージェントを用いたマクロ経済シミュレーション
大学では、物理学、特に素粒子・宇宙物理学を研究していました。
これらのテーマは一見異なる分野に見えますが、私自身は一貫して「現象の背後に潜む普遍的な原理」を探求したいという思いで研究に取り組んできました。 自然界の原理を探る物理学、思考の原理としての論理推論、アンサンブル学習の原理の解明、経済現象を引き起こすメカニズムの解明、といったようにです。
I am a researcher at Hitachi’s Central Research Laboratory.
My primary research area is natural language processing, while I also work on adjacent areas such as machine learning and economics × AI:
- Natural language processing: automatic generation of logical-reasoning corpora for improving the reasoning capabilities of LLMs
- Machine learning: theoretical analysis of the fundamental factors that determine ensemble performance
- Economics × AI: large-scale macroeconomic simulation with LLM agents
Alongside practical, industry-oriented research, I pursue more fundamental research themes.
At university, I worked on physics, especially particle physics and astroparticle physics.
I am interested in uncovering the universal principles underlying phenomena. That includes the principles of nature in physics, the principles of thought in symbolic logic and logical reasoning, and the principles underlying economic phenomena in economics.
主な研究業績Selected Research Achievements
論文誌
国際学会
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NeurIPS
Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus link
Annual Conference on Neural Information Processing Systems
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ICML
Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic link
International Conference on Machine Learning
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ICML
(Spotlight=上位5%)Rethinking Fano's Inequality in Ensemble Learning link
International Conference on Machine Learning
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SemEval
(1位)Hitachi at SemEval-2020 Task 3: Exploring the representation spaces of transformers for human sense word similarity link
Proceedings of the Fourteenth Workshop on Semantic Evaluation
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SemEval
(1位, Oral)Hitachi at SemEval-2020 task 7: Stacking at scale with heterogeneous language models for humor recognition link
Proceedings of the Fourteenth Workshop on Semantic Evaluation
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SemEval
(2位)Hitachi at SemEval-2020 task 8: Simple but effective modality ensemble for meme emotion recognition link
Proceedings of the Fourteenth Workshop on Semantic Evaluation
国内学会
招待講演
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AAAI
Can We Teach Logical Reasoning to LLMs? – An Approach Using Synthetic Corpora link
AAAI Bridge Program "Logical and Symbolic Reasoning in Language Models" keynote speech
International Conferences
-
NeurIPS
Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus link
Annual Conference on Neural Information Processing Systems
-
ICML
Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic link
International Conference on Machine Learning
-
ICML
Rethinking Fano's Inequality in Ensemble Learning link
International Conference on Machine Learning
-
SemEval
Hitachi at SemEval-2020 Task 3: Exploring the representation spaces of transformers for human sense word similarity link
Proceedings of the Fourteenth Workshop on Semantic Evaluation
-
SemEval
Hitachi at SemEval-2020 task 7: Stacking at scale with heterogeneous language models for humor recognition link
Proceedings of the Fourteenth Workshop on Semantic Evaluation
-
SemEval
Hitachi at SemEval-2020 task 8: Simple but effective modality ensemble for meme emotion recognition link
Proceedings of the Fourteenth Workshop on Semantic Evaluation